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April 28, 2020 - Clif High
55:16
critical thinking - critical numbers & future history
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Time Text
There we go.
Gain.
Yep.
Okay.
Fiddle around here for a second.
There we go.
I have a new microphone, but that's not the explanation for the difference in sound quality the other day with Paul Cottrell.
Don't know what to put that down to other than software.
I've done repeated tests with this microphone and others, and I can't duplicate that effect here on my own.
So anyway, we'll put it down to internet gremlins.
So today is the 28th of April.
It's 8.15 in the morning.
And we're going to talk about some critical numbers that have come in.
So there have been a couple of meta-studies.
You can find them out and about if you care to.
Mainly European, examining coronavirus patients outcomes, but not treatment, but tests as they presented themselves to the hospital.
So there's some things to note about all of these kinds of studies, right?
This is just like a California study that said, oh, oh, the case fatality rate is real low.
No, that study was so flawed.
It was so flawed.
It was gross.
Those people were idiots.
What they did was allow the study to be self-selecting and then they presented an incentive for people to get tested if they thought they had had it, thus boosting the number of people hugely that were going to present with it.
So they increased the positives relative to the overall population.
They distorted it by some unknown but quite massive amount.
So the California Stanford study is bogus and bullshit.
They might as well have gone on down to the local homeless shelter and just have someone pull some numbers out of their ass for all the good it does.
Anyway, though, we've got some decent numbers based on a meta-study.
Now a meta-study means that they look at facts and figures without involving themselves with the patients or the selection or any of that.
So sometimes they'll examine how the patients came to be into a study.
Usually a meta-study is done looking at other studies across many other studies on the same subject, trying to reconcile or solidify numbers or understanding.
Okay, so here we have a meta-study that is done out of actual clinical presentation data.
That is to say, this meta-study came out and there were two of them and they both reflected the same information.
One is European based and the other was, I think it was only England, but I'm not sure.
It could have had other, because it was done through the WHO in terms of the collection of the data, I'm not sure if that data wasn't polluted.
I'll have to go and look at it.
However, the data sets were conclusive and so far as what they were saying, it was rather obvious on the face of it.
All right, now in these clinical presentation studies, the metadata, what they did was to look at the data that was analyzed, or all of the tests that were taken of people presenting themselves to hospitals for treatment with coronavirus.
Now, there's something to know about that.
As we went forward into this episode of global health crises and the horrific reports came out, it became increasingly, or there was an incentive to not present yourself to the hospital because that was a bad outcome.
And a lot of people knew this in advance.
So people delayed going to the hospital, and so they would become quite severe when they presented themselves.
And a whole lot of people died without ever going to the hospital because they waited too long.
Not that the outcome would have been different had they gone to the hospital for those individuals.
And we can get into why that's the case in a bit.
But so we're looking at a, again, a self-selecting group, but this set of clinical data, insofar as the self-selection is, was driven not by an incentive to get a work permit, so to speak, a go back to work process, like in the Stanford study, but actually to obtain relief from the symptoms you were suffering.
All right.
And so these were people that were ill.
They presented themselves at hospital.
So by definition, they're not mild.
They're not in that mild case.
Now, there were some.
The number of mild cases relative to the total population within this study is very small.
So if we took this study and projected it the way the Stanford study, if we just took this one and projected it out onto the population, we would say that 70% of everybody that gets the disease will have an extremely severe case.
And of that 70%, over half of them will die.
And 30% will have a mild case.
And some of them will go into severe.
So, you know, so it's how you get the data and how you project it out.
So if we only took clinical hospital data, those people presenting themselves to the hospital with this, and then projected it out to the total population, we'd be looking at an entirely different picture.
But in any event, here's the real, here's the picture that emerged from what happened here.
It turns out there are some critical numbers.
And these critical numbers were extracted from the data.
They stand out in a huge, it's like there's a giant spotlight on them, and there's some people down there waving red flags like they're going to land giant airplanes.
Okay?
Just showing you these critical numbers that say, if you do this, you won't have this, right?
You won't get the disease.
Because it turns out there are indeed indicators that say that people are paraimune.
They just don't get it.
And these two indicators are vitamin D and vitamin C. All right?
I put the numbers up here and I'll go through and explain them.
And then we'll go into some other stuff that is tangentially related to the whole mess.
So the thing to know here is that we're dealing with actual numbers extracted from blood work.
And these are the numbers that the doctors dealt with when they found people presenting themselves in hospitals all over Europe.
And I've had to normalize a bunch of numbers.
So for instance, some medical institutions still do blood assays for vitamin D in nanomoles per decaliter.
And those had to be normalized to nanograms per milliliter.
And we've had to do some, but nothing was lost in this translation of units.
Same thing with the vitamin C. And it turns out there's an intimate relationship between vitamin D and vitamin C insofar as our current coronavirus episode.
There's an intimate relationship to the linked relationship to health.
As we know, from those people that supplement with vitamin C and vitamin D, you feel better.
You don't get ill as often.
Well, here's proof of it.
Turns out, of all of the people, and let's, I think there were, I have to do a quick calculation here.
There were three groups comprising a total of 1,100 people in the two studies.
And what we end up with is a sure indicator, even though that's, you know, basically 1,100 people, but split over three studies, so say 387 people per study at a maximum population or maximum universe is still small relative to the total population of the planet and humans.
However, it's much better than 12 people, right?
And so what we find is that given the severity of the disease, right, those people that presented themselves, what do we have happening here?
Hang on.
Okay, those people that presented themselves to the hospital in the severity either of at the time of presentation or the severity of the progression of their disease in the hospital.
So in both of those metrics.
So if they were feeling bad, if they were, say that you took the little hospital chart where it's a little happy face all the way up to a sad face and it's a 1 to 10.
So if they were presented themselves at a 6 initially, they would show up within this category.
But if they presented themselves at a 6 and then later on they were at an 8, they would show up in this category.
Then, if they were at 10, and then if they passed from the disease, they would show up down here.
So you've got severity of the progression of the severity as well as the presentation severity.
So both of those were included in this extract of the severity issue.
And so without regard to anything, just examining the severity of presentation, there's 100% correlation.
You know, and they were saying it's not causal or any of that.
We can just let that aside.
100% correlation between vitamin C and vitamin D levels and the severity.
All right.
And the cross-correlations were rather interesting.
So first, let's just get to the big numbers.
Anybody that had 40 nanograms per milliliter or greater never presented, was never seen.
Let me get a marker here.
A couple of these things.
Okay.
Okay, so it was 0%.
And now, let's bear in mind some things here.
The mainstream medicine, right?
MSM thinks, used to think that anything over 20 nanograms per milliliter was toxic levels of vitamin D. And then they gradually got to the point where they accepted that 30 nanograms per milliliter is normal, all right?
Normal, not optimal, just normal.
And so that was their assumption as to what the normal barrier was, the boundary down here.
And what they discovered was everybody that presented to them, most, almost all of them, so 96% of the people that presented themselves with the disease at the hospital fell within the category of normal vitamin D levels or deficient.
All right?
But nobody with what the allopaths consider to be abnormal vitamin D levels presented ever.
So that means that nobody with 40 nanograms per milliliter of vitamin D is ever going to get, or is getting this disease.
You can't say they're not ever going to get it, but basically they are not at this point showing up at any hospital.
Ergo, the instant conclusion is if you can raise your vitamin D level to this right here, absent and disregarding almost all other criteria, it would seem that that would be a pretty good indicator you won't get the disease at any level of severity.
So you had zero severity, zero presentation at that level or higher.
And they actually consider people at that level to be at risk now of vitamin D toxicity.
My level right at the moment is 70 nanograms or higher.
Okay, so I'm up here at 70.
At 64 nanograms of vitamin D per milliliter, you find lifeguards.
Lifeguards and what they call wet body surfers.
That's surfers that are in warm waters and they don't have to wear wetsuits, okay?
So here, let me put that better.
Okay, so that's what you usually find there.
But I was trying to raise this up because of the anti-cancer component of it and discovering that our ancestors, as recent as 30 and 40,000 years ago, and still represented by hunter-gatherer societies that we can find today, will have 120 nanograms per milliliter of circulating vitamin D with D3 with no problem whatsoever.
Healthy.
Also, vitamin D is known as the happy vitamin.
All right, you feel happy, jolly, you know.
You know, okay, you're in a fight, but you're happy about it.
So anyway, so vitamin D is good stuff, and that's where I was headed.
And so it likes, well, geez, it would appear, in spite of the chaga caught in my throat, that I wouldn't have to worry about it because I'm higher than the 40 nanograms per milliliter.
So that was like a baseline that was really solid on this, okay?
And then for people that presented also, there was a correlation with, again, with presentation severity, with severity of progress, and the amount of vitamin C assayable in the system.
And so it was at 0%.
There was nobody that presented with one milligram per decaliter of vitamin C, active circulating vitamin C. Vitamin C is difficult to measure.
They use different measurements.
It was difficult to normalize across studies.
They assay different aspects of vitamin C. It only lasts 24 hours in your system.
Vitamin D and an active phase can last only minutes, but you have vitamin D receptors throughout your whole body, and so you'll always have a certain amount in the body in a way that you don't with vitamin C. But in any event, with the vitamin C, I translated it over here.
And so they did not ever have anybody present that was taking vitamin C at the level that the Chinese had recommended for their sailors.
Okay.
And I translated that to English, standard American units here of 22 milligrams per pound.
So at that level, nobody ever presented to the hospital with any aspect of the disease.
At a level of 13 milligrams per pound, which was what was considered optimal prior to the release of the COVID-19 on the planet, it was considered optimal by those of us that were into optimal vitamin levels.
13 milligrams per pound was considered to be an optimal level every day.
And that was in the rare category, where they had one or two people that presented at that level, but they never, never, these guys here, in both cases, never progressed in severity.
They stopped just with presentation at the hospital.
Whatever initial treatment they received, they received.
They didn't return.
They didn't have a bad outcome.
So these categories right here, above what is considered normal for these vitamins, show as a critical number for extremely good outcome, right?
The good outcome is to either not present to the hospital because you're healthy and you don't need to, or if you do present, you take whatever initial treatment you get and then you go away.
Now, in spite of the fact that we had people at these levels show at the hospital, they had other comorbidities.
They had other contributing factors.
And so that's probably, you know, we can't say for sure, but that's probably why they ended up presenting at all.
Nonetheless, even with those comorbidities, whatever they were, among those 387 people in the different groups, they still ended up with a good outcome.
So this was a good, these are good numbers right here right now.
Above that, you have a quality good outcome.
And so presumably anything higher than the 22 milligrams per pound on vitamin C, which would be anything higher than, say, eight or nine liposomal vitamin C's a day for someone who was 200 to say 220 pounds, would be blazing you up here in the never going to see you at a hospital again, you know, that kind of thing, right?
So very good.
This is what they considered to be normal.
And everybody that presented to them in the hospital and all of the people that presented at the most extreme risk, which was 92% of everybody that presented, had a combination of subnormal vitamin C circulating and subnormal vitamin D circulating.
Some of these people were deficient down to the point where they were near ricketts levels.
So we're talking down to four nano, I need a different color for that.
Four nanograms per milliliter.
And also in vitamin C levels over here, it was just abysmally low where we're talking not something, not six milligrams per deciliter.
I mean, way down there.
And so, but either case, so as as so it was predictable from an actuarial viewpoint that as your numbers of vitamin C and vitamin D were deficient and proceeded towards deficiency, so your odds of ending up in the in the nasty outcome group exponentially or rose in concert.
So their inverse relationship or direct relationship.
Bad numbers in vitamin C, bad numbers in vitamin D equals bad numbers from the COVID, from the disease, from the bioweapon.
So, interesting, factual, current, not likely to change in conclusion, although the numbers are likely to change in terms of the numbers of people being assayed going into the various hospitals.
And the reporting of the numbers coming out will be much, much greater now that we're getting further into this.
More hospitals will have the time to collate the numbers and put them out there to where other people can get at them, start aggregating them, do the cross-referencing, and start coming up with some of this stuff.
So, it was very illuminating.
It was nice to wake up this morning and see this, to be able to go and look at some of the conclusions that the French and the I think they were Czech Republic researchers had done on the one study.
Now, and they were of the so the Czech and I think it was French and Czech.
Anyway, but they were of the opinion that we won't ever see surfers or lifeguards.
They'll just never ever ever show up because they're at a threshold so high at 64 nanograms per milliliter circulating because they're out in the sun all day.
That they know that the virus is just not capable of getting at them.
And this, a lot of this makes sense, okay, because vitamin D and vitamin C are related to the accessibility of the ACE2 receptor.
The vitamin D pathways are in every cell, they bind in every cell, they in many cases prevent other things from binding in terms of viruses, and that's why they're basically an antiviral.
And vitamin D is also used as, well, also vitamin C are used as anti-cancer treatments in and of themselves now to great effect.
So, anyway, so this was the takeaway, and it's very good news indeed.
It means we spend more time out in the sun and get as you know, get as much sun as you need to maintain your vitamin D levels way up.
You can get tests, so you can go and get blood tests and just pay for it and find out what your levels are.
That's how I found out mine was at 70, and I was trying to raise it up.
And it was actually that level at that last meeting with the oncologist that had the guy freaking out.
He was quite convinced out of his abysmal ignorance of these things that I was going to keel over dead of vitamin D toxicity within mere hours, if not mere days, if not hours.
You know, so he just didn't have a clue, but he knew it was, he was of the opinion that normal was down here, and that really freaked me out.
So, anyway, so I had to fire him, couldn't deal with that guy.
All right, so let's see, there was that.
Okay, so now the other thing out of the study there, the other chief indicator or the other chief conclusion that came out of the study here was that obesity, and in a more complex form of that statement,
a bad diet, processed food, high salt, high sugar, is the chief indicator of extreme risk of extreme bad outcome.
Of course, we note that if you've got a bad diet, you're down here with deficient in vitamin D and deficient in vitamin C because you're obviously not supplementing and you're not getting anything out of the food that you're eating.
And so, the direct correlation of the two is notable and very predictable.
Again, the correlations are not ironic, it's you know, it's like slap you in the face, obvious.
That if we have this situation here where vitamin C and vitamin D are not being consumed in your regular diet, you become deficient, then you end up done in this category.
And guess what happens?
They put us all into quarantine, and you can't get at your junk foods anymore.
You don't have people in the restaurant business feeding you the seed oils, everything's saturated with salt, etc., etc.
You're forced to rely on eating at home, even though you may eat, may consume junk food at home.
At some point, you have to transition into something closer to real food.
You start cooking more for yourself because you're bored, you eat a higher quality of food, you get more vitamins, you're less at risk, you get healthier, blah, blah, blah.
It starts so there's a combination of a dampening effect all around.
Not only, so a contributory effect from the shelter at home is that people are going to end up eating better, whether it's initially or not, and that will dampen down some of the risk in the general population.
Plus, they'll have more time to get out into the sun and eat that orange or whatever.
So all these lifestyle changes forced by the shelter in place also go boosting us into better numbers, way up here above the critical numbers.
Of course, they're not assaying for chaga.
There's a lot we've discovered.
I'm taking a couple of virology classes now to really delve deep down to how the chaga probably is working.
It's very interesting, even the virology classes, I have to say, are quite interesting themselves.
But in any event, so we know all of this is in play at various different levels all the way around.
So if indeed we're sheltering in place and we eat better because of that, up to the point that we can't get the junk foods, and so we all have to concentrate on real food, and all the junk food starts waning itself out of the diet, then we get a rising tide of healthier people due to eating better,
and then all of a sudden we have supply chain disruptions and we're worried about that, so we have to grow food ourselves locally, which boosts the percentage of the population that have a much richer diet with minerals, et cetera, et cetera, which makes that level of our population that much healthier and raises us all up over these, quote, normal levels.
So in general, the shelter at home and the, in general, the destruction of the disparate long global supply chains is, in general, a good thing, right?
It's a bad thing for all of us to have to go through because of the disruptions, the changes, etc., the adjustment and so on.
But at an individual level and at a collective level for health, it is better in a long-run sustainable fashion, especially going now into the ice age.
And so I'm going to go ahead and take this off.
So let me back up.
And if you wanted to get a screenshot, you can go ahead.
I don't know that you would want to.
The tests are out.
You can see a number of people reporting on them.
So anyway, let me get this out of here.
Okay, so that was our critical numbers.
Now we're going to go on to future history.
All right, so in looking over the emotional range data from the old reports, which was this running log of building and release tension numbers on aggregate bundles of words.
But in looking over the old data for the period of time as it was described in the reports, not the timing, because the timing was off probably by a year, year and a half or so, at the earliest on some of it.
Bear in mind that we're looking at events being described that are in kind of an ellipse.
And we're back here, all right?
And so these events are all coming at us this way.
They're not all going to, we're not going to encounter the big mass of events and end up right here in a jump.
It's an incremental day by day by day by day by day by day encountering.
So the emotional toll taken on us by our encountering all of these events shifts moment by moment by moment, making up the aggregate of the projected day by day values that we would end up in terms of hitting this.
All right, and then so the way that our data sets always worked.
If this thing actually bulged out.
All right, let me redo that.
just to make it more clear.
Okay, so we're right here.
And we'll consider this as our current now.
What I call the ever-present now.
Okay, and so we're right here, and our future can be thought of as a cone that stretches off ahead of us into which all kinds of events are going to fit.
And we can think of those events as approaching us as kind of like a bulging out kind of a shape.
All right.
Now the way that our data sets work, I was not able to ever predict how it would look on the back side of any big bulge.
So conceptually trying to get this across is very difficult.
So the events, for instance, could cause emotional ripples that would end up looking like that.
And there would be no way for me to be able to predict based on the way in which our data went.
All I would get is a generalized sectional analysis that projected out the intersection of these guys there.
The intersection of these elements as they encountered our projected cone of the future.
Hang on.
So this is basically what we would get in terms of numeric values, right?
These would be release tension, and these would be building tension.
And it didn't matter.
It was just the way I labeled these things numerically.
This would be the mass of the words that describe the events that we would be going through that would present these intersectional numbers.
And so this was a range of how that thing was going to hit us.
Now, as any individual within the mass of humanity, you might be anywhere in this range, but the way in which the data projected it, you were unlikely to be outside the range and unlikely to be experiencing that time and event up in here.
In a general sense, you would be within this mass of humanity.
And you would be experiencing, it was possible to sort of cite individual kinds of clusters of words somewhere along this range of building and release tension values.
Clear?
Clear as mud?
Okay, so the descriptions were extracted from the data sets, the old data sets, not the individual language so much as the numeric values that surrounded each of these language clusters, our related groups, our attributes and aspect associations.
So the projection is around those, we can make projections in a general sense about the emotional values of humans and what we're likely to experience as we go forward through time.
All right, so it's possible to, and this is independent of when this time period started.
Okay, so basically what I'm saying is that just because the old reports projected a certain thing to start in 2016, if those words and that projection was, if the projection was off in timing,
but the construct of that event segment was valid, then those projections that can be made about that segment can be made about it at any point, regardless of whether it showed up in 2016 or 2020.
The value of the or the quality of the description is still valid.
So this element right here might appear in 2020 as opposed to the 2016 that was forecast because our timing values were off in the report, but the descriptors still line up to the descriptors that we saw within the related set.
And so we can make certain assumptions and we can always put if valid, if valid.
So we're making assumptions that the data set that was described that was seemingly accurate for the sun disease, let's just call it that here, Which we now translate to this,
is able to be projected onto time, and we can just eliminate the 2016 as the starting point for it and say, oh, okay, it actually started off in late 2019 in China, but for the rest of the world was basically a 2020 event.
And so the sun disease started manifesting within this period of time, but still the relationship between the individual elements is unfolding as was projected.
And so it's like, oh, okay, you know, we have a number of things that we can fall back on that validate that the set is still manifesting.
So for instance, we've had hits on, you know, vitamin health and old-style traditional Chinese medicine working and so on and so on, and the way it was going to pop off.
So we've had a number of these elements show up, which indeed have been manifesting in reality as had been forecast.
So this gives us some confidence that projections that we might be able to make for the rest of this bubble that had been shown here and had been described in previous reports or previous time period might still be valid.
We won't know until we get through it all.
However, it actually frames a nice way to frame our scenario planning to say that, well, look, we've had three out of 11 or 3 out of 20, whatever we identify within the data set as having matured, having manifested, the others were still in a progression, still out there to be seen.
And so we await the other manifestation or not, and we tick them off or say, no, this one didn't happen.
However, it gives us a scenario or a timing clues for the scenario planning that we're doing in examining this particular element as it was supposed to present itself to us.
And so we can make some projections here that, okay, so it started showing up in January, really out in October of 19.
And that's important, all right, because it didn't start manifesting in the West.
It started manifesting in China, and we are on sort of a counter because within the data set here, which is extracted from this element, which would have moved over to our ever-present now, which is referenced as right here, and we're looking at this, within this set here, there were referential, there were temporal referential elements.
So in other words, within the data set itself, it had language referencing how long certain events would take and would last and that sort of thing.
So within this data set there for the sun disease, we're told that the sun disease appearance has three, it'll pass around the planet three times, so it has three waves.
The first wave is the most shocking, but it's actually the least in terms of potential impact and damage.
So it was not to be the most nasty or whatever.
And that's why it's worth fighting to get people to pay attention to derail some of these projected reactions to this forecast information, which is all we're doing, right?
We're just sort of monkeying about with time and how humans were forecast to react to certain events.
The events need not happen if we sort of like suck the energy out of it ahead of time by altering things, right?
In other words, you need not see a train derailed if you see a spike on the track and you're able to flip the spike out of the way before the train gets there.
You can alter the future.
And in that sense, you might alter the future for everybody that was on the train and for everybody in the nearby town because those giant tanks of chlorine dioxide would not break open and gas them all to death.
Anyway, so here we have some descriptors.
But what's shown to us is that this first wave, which is actually the least damaging through mortality, is going to last for 12 months.
So we've got one year, and it's the second half of that year that is the really terrible part.
So the first six months are not as bad as the second six months.
And so this is the area that we want to concern ourselves with because that's still ahead of us.
We're still within the first six months of this event.
Now, we're going to start calculating this, though, from the time that the event came into generalized or could have been perceived by large numbers of people to start generating the emotional boundary numbers.
All right.
So China's a big place.
So we're going to take the event as having begun from when the emotions started overwhelming people in China, which really was over here in December of 19.
But for our purposes, that's so close, we might as well just say January is our incept date for the whole big thing rolling out, which means that what we're looking at is that this first wave issue here, we're going to have to be concerned from June onward, because it will get really bad from June onward.
Now, it's not necessarily the way that these things work, an increase in the number of people that are ill.
It's not necessarily an increase in the number of people that are dying from it or any of those kind of elements, right?
It could be that the things that make this emotionally worse, and this is what we're talking about, is release emotions.
Okay, so this is release emotions.
And the value of the release emotions is rising, which basically means you're screaming louder kind of thing.
So the release emotions are rising, but that's a, in this case, that's a net negative effect because the release emotions relative to this event are below our median line.
And so, oh boy, this gets complicated, all right?
So basically, as we go forward from the solstice, all right, so let's just pick that it's going to be the 2020th onward, and it's probably closer to the very end of June, 29th, 30th of June, something like that, is where we'll really start seeing the language pick up because of the gaps, the separations within these subsets as we go forward.
In any event, though, so from there till the end of the year, it's going to get real rough.
Now, it may be that it's the supply chain breakdown really hits us from July 1 forward, right?
So let's make this the end of June right here.
And so that'll mark us another clear boundary.
Somewhere in those last 10 days of June, there'll be some kind of a hard boundary that we'll go across the same way we had a hard boundary where we had pre-knowledge, where you're walking along in your world, everything's normal, and all of a sudden you become aware of the disease having been released.
Whether you know it's a bioweapon or not doesn't matter.
You know that the world changed at that point.
The novel disease, all of a sudden it's flooding into your information.
There's new emotions showing up.
Everybody around you has knowledge of this.
And then you look all around and your world has changed and is changing.
So that kind of shit is going to happen again sometime in the last 10 days of June, more or less, right?
You may not become aware of it until July because maybe your world actually changed in March when you were locked down because you had your head off in some video game or something else making money or whatever the hell and you weren't paying attention and all of a sudden boom lockdown.
Okay, so it depends on how you encounter it as to how you're going to experience this one as well.
In this case though, the projection is going to be that it's going to be globe affecting again, that it's going to occupy us continually through to the end of, actually to the end of January of next year, sometime in here.
Let's just say the middle of January, okay, so we'll just say January 15.
So up until January of 15, there's going to be this block of time that will be emotionally more intense than what we've gone through in the first part of this year.
Could be war.
Could be that we all get really pissed at China and everybody goes to war with China.
Could be that there's a giant civil war in China that has us all freaked out.
Any number of things not necessarily directly disease related could be the cause of the descent for the population as we go forward into increasing release language.
And I didn't draw this right.
It should have been disproportionately deeper here.
So more release language than building language.
And so building tension language.
And so, but in any event, so we'll have greater amounts of volume of release language showing up over the rest of the year.
And the way that it works out, let me draw a quick thing.
Okay, so the way that it actually plots out.
It looks like this as we go forward.
You have different as so you have word groups that morph and as they morph from one set, as you encounter them over time, they morph from one set into another set of words, but you're still heading in a expanding volume of release language downward as you go forward.
And so until we get past this area right here, some point out in the future, which is three years out relative to that forecast back in the old reports when we had the data sets running, which had originally pegged it in 2016, thus would have been three years out to 2019.
It's actually 2020, so we're out to 2020.
It's the beginning of 2024.
So this is three years right here that it's going to take us to get through this lopsided release language dominating building tension language period.
And obviously now we know that a lot of this down here is related to the disease, the fear of the disease, the impacts of the disease, the destruction of the supply chains, and so on and so on.
And that's our progression.
Now, we need not have this area here occupy us with disease if we just make decisions, change our vitamin C and our vitamin D levels across our nation, have the social order pivot right away and start getting everybody shouting at everybody else, take vitamin C, take vitamin D, blah, blah, blah.
We can change the actual narrative that's going on in here.
Now, we'll still have release language that we're going to have to live through in the sense we're going to still have to deal with the supply chains and so on.
But after we get past this point right out here, we can change the shape of it and alter the building language again very rapidly, changing our projection through time because this out here is not able to be assayed the way that this was.
So we could actually come out to this point here, have it rise very rapidly, like that sort of a triangle, right?
Sort of a sail.
And head on up here into building language to compensate for and overcome the problems that were created in this period down here.
This is totally unknown.
It's up to us to decide how to do that.
But our data did project that we've got to go out this three-year period of time before we get beyond this.
Now, within that three-year period of time, there will come out those things that are going to cause this line to alter or to shape it and cause this next bubble of impact of events to take shape as we're going from one to the next to the next.
All we have is a projection out to these three years.
We know some things, some other projections, you know, ice age and a few other things, but these are so vague and so, or not vague, they're so broad and broadly applicable that we don't know how we're going to relate to them and whether it's a positive release language like, hey, hooray, hooray, let's party.
We got through it, or a negative release language like, oh, damn, you know, Sam's dead, that kind of thing, right?
So anyway, so this is what we've got.
I'm at this point, I'm Most focused on the June through January period.
The things we can do now can set us up for June, just like the things we did in January, set us up for what happened in March.
So we can get our gardens going.
We can really concentrate on continuing good health practices that take us out of the risk category and get us back towards basically the caveman approach, right?
Get our vitamins and minerals and stuff up to those levels, and the bioweapon cannot apparently impact you at all.
So, very good news.
I mean, they saw nobody with 40 nanograms per milliliter or higher of vitamin D. And consequently, they saw no one who was effectively also supplementing with vitamin C. Because usually, the people that are going to supplement with vitamin C or vitamin D to sufficient levels to achieve the step out of normality defined by mainstream medicine are going to be so healthy that they're with one, they're also doing the other.
You just don't see people take vitamin C and no other vitamin as a rule.
So, anyway, all good news.
We're preparing for this next round.
It eases up on us as we go forward from there because our data sets projected that rather than flattening down or something, so the building language of those sets could have just dropped down to nothing here, could have all gone down this way.
Instead, we see that gradually over these next three years, we're getting to a point where the building tension language in a positive fashion was rising and was starting to dominate to you know to equal and dominate the negative release language.
You can see why I never charted this shit.
People just, it's very difficult to understand because you've got so many different axes going on and elements involved.
So, anyway, so this at the end of that three years, I mean, I'm optimistic.
Yes, I'm taking my vitamin D, I'm taking my happy vitamins, so I feel good about this stuff and I'm ready to fight, even though it's a fight, I'm happy about having the fight.
But nonetheless, it's like, okay, guys, I'm reasonably optimistic.
You know, it's almost into June.
June's going to be really interesting to see what we've got waiting for us then.
A new challenge, you know, things are going to happen.
Destruction of the past, invention of the new, release of the ancient information.
All of this kind of cool stuff is ahead of us.
We have, when we look at time, one last thing before I shut down here, this has been going way too long.
Sorry to take up everybody's day.
When we look at time, as we go forward in this year and slightly into next, we have this emotional data set from the old data that went sort of like that.
And then afterwards, was sort of like that.
Let's just say that this is where we are here in April.
This was in late summer.
So, say, August 1 onward.
This would have been like the end of October, maybe or early November.
All right.
And this is an emotional kind of a thing.
Now, it's still all this negative emotion, and it's still all of this release kind of emotion.
But as we're moving forward, this right here represents one of these data elements down in here.
So let me dash lines over.
And so that would be like an expansion of the emotional trail on one subset of the master dominating set.
Okay.
And so this would be expanding on what I had called sci-fi world.
And in this case, what we're looking at here is reverse engineered tech and real ancient history.
And those two together, those two sets together, were rather inclusive of any number of woo-woo subjects.
And they're going to be involved in this transition of this emotional set over a very short period of time for vast numbers of people.
So, this was what we could postulate meant that there was some kind of an up-chucking, a release of the information about these two things within the general social order here.
And it was suspected at the time, at the time that the report was prepared, I suspected that what actually was going on, that it was an act of desperation because of all this other language that was there.
I could have pinned it on the USA government reacting in an act of desperation, releasing this kind of information in order to try to shift the perception mechanics of the social order such that we started building more and more positive emotional trend lines, so to speak, right?
So, because it promoted hope, there was an instant flowering of hope as the technology was described, blah, blah, blah, blah, blah.
Yeah, it was disruptive, but even that disruption was good because of the way that it broke open certain loggerheads, certain log jams, that kind of thing in terms of people's emotions.
So, anyway, so we still have this potentially waiting for us because this was within the sets that we're now operating here in Sun Disease for, well, actually, for this period right here.
And so, this is still pending.
Some of the key elements, the incept data, the key data sets for sci-fi world.
And it's like, well, damn, you know, maybe George Jetson fly around in, you know, houses in the sky, all of that kind of stuff is still pending for us.
It'll be interesting to see.
Thanks for listening.
Sorry about taking so long.
The first part was the important part.
The rest of this, it's like, you'll live through it.
You'll be able to decide if I was correct or not in the future.
So, you know, but if you're thinking about things ahead of time, then at least this gives you some time frames to, and some way of conceptualizing what we still have yet to deal with over the course of this summer and then especially the latter half of this year.
And it's going to be really cool.
I mean, you know, hey, far better to be alive than the alternative.
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