@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
1-1/ @Daoyu15
And of course, neither the market can be blamed—all the wild animal stalls just have Homo Sapiens as the species that retained positive correlation with the SARS-CoV-2 where it was found—
And nor were H5N1 spilling over into humans any time soon. It is strictly
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1-2/ @Daoyu15
enteric in the current panzootic, killing all of the wild animals that the virologists are trying to blame and without causing a single spillover to humans.
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@Daoyu15 1引1-1/ @Daoyu15
Yes. They are really there defending GOF research and their grave COI making them wholly opposed of even the idea that a pandemic can ever be initiated by virology research. We need to #defundvirology #endGOFresearch https://www.bmj.com/content/344/bmj.e2398
You can only have
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@Daoyu15 1引1-2/ @Daoyu15
GoF work generate a viable prediction or a vaccine if the next emergence is of the exact same genetic makeup as your GOF strain. The extreme diversity of viruses mean that you have (total number of viruses in the world (billions)*probability that a GOF study
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@Daoyu15 1引1-3/ @Daoyu15
result being used maliciously (>1/200 minimum)) times higher likelihood that GOF research cause a pandemic in stead of preventing it.
archive.ph/BToZR archive.md/YYIXp
https://gab.com/Flavinkins/posts/109663743902085653
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 2-1/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 2-2/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 2-3/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 2-4/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 2引1-1/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 3-1/ @Daoyu15
And we do have proof of intent now.
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@Daoyu15 3引1-1/ @Daoyu15
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4-2/ @Daoyu15
https://gab.com/Flavinkins/posts/109821678549991492
The entirety of China “Huanan market” data is fabricated. Don’t be fooled.
The GISAID archive.md/0aHWr archive.md/7XL5h neither do proper versioning or China maintain any custody of “data” they put up. Nor was GISAID itself.
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@Daoyu15 4-3/ @Daoyu15
There is no credibility at all in highly politically significant “data” released by China.
archive.md/52DyQ archive.md/B0xlW
The total number of contigs in the “Q* samples” are in Inverse correlation with the product of Homo Sapiens and SARS-CoV-2.
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@Daoyu15 4-4/ @Daoyu15
archive.md/bK5mh
There is systematic manipulation of early cases data by China.
And there are accidentally released non-politically-significant data that exposed the exact opposite of zoonosis happening in China—pre-Huanan SARS-CoV-2 not in animals or
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@Daoyu15 4引 @Daoyu15 X1-1/
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@Daoyu15 4引 @Daoyu15 X2-2/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149375/
135/92 cases in early peer-reviewed papers that went missing in the WHO report, if the Chinese early cases data were “perfect and unbiased”? The missing cases represent cases that China really doesn’t want to show. Intentional removal
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@Daoyu15 4引 @Daoyu15 X2-5
the reason why they refused to provide this data in any detail at all.
Up to one third of all cases were either removed completely or moved toward the market in the “dataset”.
archive.md/zUD1F archive.md/Pc6gp
archive.md/GvRcD
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@Daoyu15 4引 @Daoyu15 X2-6
archive.md/ZgVzp Wuhan authorities after that archive.md/OIGPz 2014 incident now targeted only the Huanan market when looking for EID outbreaks—and nowhere else.
archive.md/1x658
They tampered with the early cases data
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@Daoyu15 4引 @Daoyu15 X2-7
archive.md/Ea0Kw
To make it look like it “started at the market” when in reality the first case they ever admitted lived right next to the WIV BSL-4.
archive.md/5sdkR severe discrepancy happening December 2019 and January 2020 indicate tampering
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@Daoyu15 4引 @Daoyu15 X2-8
with case counts.
archive.md/1pcCU
This is indicative of catastrophic ascertainment bias was going on.
Also, the Jan 01 jump is Onset date jump and not diagnosis date jump. Onset date, as in personally reported onset dates and NOT the “date of the first
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@Daoyu15 4引 @Daoyu15 X2-9
medical visit”. This is evidence of gatekeeping. Even if first medical visit or diagnosis dates can be artifacted, the onset dates don’t, and the then later Jan02-05 curves does not support this claim—it was not a single burst as from some mischaracterized onset
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@Daoyu15 4引 @Daoyu15 X2-10
dates data. The onset dates before 01/01/2020 was in fact censored and only those that the WMHC initially allowed, then what that is reported before 18/01/2020, were present in this “dataset”.
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@Daoyu15 4引 @Daoyu15 X3-1
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@Daoyu15 4引 @Daoyu15 X3-2/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X3-3/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X3-4/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X3-5/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X4-1/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X4-2/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X4-3/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X4-4/
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4引 @Daoyu15 X5-1/
Belt and road, not Huanan market.
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@Daoyu15 4引gab1-1/ @Daoyu15
It is clear that both the CCP and the WEF(which established the improper and deadly early pandemic response/treatment through Metabiota and Callahan , and is involved in at least a part of the virus hunting efforts for gathering sequences used to create
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@Daoyu15 4引gab1-2/ @Daoyu15
SARS-CoV-2 https://archive.md/piWba , have seeded viruses (and possibly staged “fear videos”) at least twice to generate a response ending in their desired policy outcome) desired and demanded the establishing of an authoritarian global government.
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@Daoyu15 4引gab1-4/ @Daoyu15
is now a 46 page document that includes proposed amendments to the International Health Regulations (IHR).
The proposed amendments would:
Change the overall nature of the World Health Organization from an advisory organization that merely makes
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@Daoyu15 4引gab1-5/ @Daoyu15
recommendations to a governing body whose proclamations would be legally-binding. (Article 1)
Greatly expand the scope of the International Health Regulations to include scenarios that merely have a “potential to impact public health.”Seek to remove “respect
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@Daoyu15 4引gab1-6/ @Daoyu15
for dignity, human rights and fundamental freedoms of people.” (Article 3)
Give the Director General of the WHO control over the means of production through an “allocation plan for health products” to require developed states parties to supply pandemic
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@Daoyu15 4引gab1-7/ @Daoyu15
response products as directed. (Article 13A)
Give the WHO the authority to require medical examinations, proof of prophylaxis, proof of vaccine and to implement contact tracing, quarantine and TREATMENT. (Article 18)
Institute a system of global health
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@Daoyu15 4引gab1-8/ @Daoyu15
certificates in digital or paper format, including test certificates, vaccine certificates, prophylaxis certificates, recovery certificates, passenger locator forms and a traveler’s health declaration. (Articles 18, 23, 24, 27, 28, 31, 35, 36 and 44 and
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@Daoyu15 4引gab1-9/ @Daoyu15
Annexes 6, 7 and 8)
Redirect unspecified billions of dollars to the Pharmaceutical Hospital Emergency Industrial Complex with no accountability. (Article 44A)
Allow the disclosure of personal health data. (Article 45)
Greatly expand the World Health
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@Daoyu15 4gab1-10/ @Daoyu15
Organization’s capacity to censor what they consider to be misinformation and disinformation. (Annex 1, page 36)
Create an obligation to build, provide and maintain IHR infrastructure at points of entry. (Annex 10)
The 76th World Health Assembly is scheduled
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@Daoyu15 4gab1-11/ @Daoyu15
to occur from Sunday May 21, 2023 to Tuesday May 30, 2023. In order for the proposed amendments to be considered during the 76th World Health Assembly, they must be submitted to the World Health Organization at least 4 months in advance.
The IHRRC plans to
@zijizhanchu_5 - 🇺🇸找出病毒真相-5🇬🇧🇯🇵🇨🇦🇺🇦🇮🇱🇰🇷🇩🇪🇫🇷🇮🇹
@Daoyu15 4gab1-12/ @Daoyu15
submit these proposed amendments to the WHO by Sunday, January 15, 2023.
The International Health Regulations are existing, legally-binding international law. If the proposed amendments are presented to the 76th World Health Assembly, they could be adopted
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@Daoyu15 4gab1-13/ @Daoyu15
by a simple majority of the 194 member nations.
According to the already agreed upon rules of the IHR, if the proposed amendments are adopted, the member nations would not need to take any additional actions. The United States Senate would not be required to
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@Daoyu15 4gab1-16/ @Daoyu15
powerful players — the World Economic Forum, the Bill and Melinda Gates Foundation, and the Wellcome Trust — have rallied to form an organization called the Coalition for Epidemic Preparedness Innovations, with the goal of finding ways to help fund the
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@Daoyu15 4gab1-17/ @Daoyu15
creation of vaccines that are badly needed but not likely to turn a profit for drug makers.
And a pilot project that has been underway for the past seven years — called PREDICT — has discovered about 1,000 new viruses.”
A common link in Metabiota was once
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@Daoyu15 5-1/ @Daoyu15
So unfortunate. China have tampered with their data and all their “zoonosis” reports are there to cover up their deployment of the SARS-CoV-2 bioweapon.
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@Daoyu15 5引1-1/ @Daoyu15
In fact, it is one of the reason why the actual correlation wound up negative with animals and positive with humans—these samplers are what that ended up shedding it into the market. A20 first, then all of the lineage reads-free “wildlife stall samples” came from
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@Daoyu15 5引1-2/ @Daoyu15
a contaminated boot (to the surface) or a contaminated suit surface (to the sample tube).
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@Daoyu15 6-2/ @Daoyu15
Superfluous, in human metabolic products and secretions, and not in butchered tissues. They are cleaned off and degraded efficiently. The animal native viruses are inside the tissues and are highly persistent—class of contaminant type different and SARS-CoV-2 is
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@Daoyu15 6-3/ @Daoyu15
in the class that is inconsistent with the behavior when pitched against cleaning than animal CoVs.
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@Daoyu15 7-1/ @Daoyu15
Lastly, the touchstone for distinguishing between spurious correlations, confounded cariables and genuine causation is to narrow down to specific slices where the test item is present and check correlation—a genuine causation is correlated in the same way in all https://t.co/6H0odMWHiS
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@Daoyu15 7-2/ @Daoyu15
slices, like Homo Sapiens, and spurious and confounded processes crashes upon narrowing down to slices where the analyte (virus) are present one way or another, sooner or later.
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@Daoyu15 7引1-2/ @Daoyu15
products and secretions, and not in butchered tissues. They are cleaned off and degraded efficiently. The animal native viruses are inside the tissues and are highly persistent—class of contaminant type different and SARS-CoV-2 is in the class that is
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@Daoyu15 7引1-3/ @Daoyu15
inconsistent with the behavior when pitched against cleaning than animal CoVs.
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@Daoyu15 8-1/ @Daoyu15
similar to this,
Spurious correlation arise from common cause—time in case of temperature and pirates, proximity to toilets in case of posteriorly isolated species and virus in all samples. Just like for many different variable there are always those that correlate https://t.co/wgk7FpjFGy
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@Daoyu15 8-2/ @Daoyu15
well with time, when all PCR+ samples are in one location closest to the toilets from entirely unrelated cause (sampler boots and suits contamination where closer to the toilets mean more direct entry into the stall after entry into the market, where fresh virus https://t.co/3puTkNipMk
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@Daoyu15 8-3/ @Daoyu15
is on the boots and suits to contaminate the samples) there is one or two unique (found in less than 3/7 of wildlife stalls) species in every stall and the majority of animal sales are on the ground.
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@Daoyu15 9-1/ @Daoyu15
The way they adulterated the post-26-03/2023 datasets is also one of the reason why the jbloom et al datasets gets humans as higher ranked in the alignments in the positive samples compared to all samples in both all and Jan 12—They do it by dropping random human https://t.co/j9L6OaF0CV
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@Daoyu15 9-2/ @Daoyu15
reads into the “negative samples”, all uploaded after 26/03/2023, resulting in an reduction of spread and correlatedness with humans for all samples compred positive samples only.
In fact, all 3 samples that are different between 2021 and 2023 are also samples that https://t.co/gbE0wmeEEJ
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@Daoyu15 9-3/ @Daoyu15
have additional datasets uploaded in 26/03/2023 after an 03-10/03/2023 upload. Sample A20 have distinct host composition between the 03-10/03/2023 (without lineage reads) and 26/03/2023 upload, which is not expected from “viral amplicon sequencing” (with lineage A
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@Daoyu15 9-4/ @Daoyu15
reads) which does not perturb the host reads if genuinely from the same sample.
In extremely spatially biased conditions such as in Jan 12, two aspects happen: 1. Human reads and reads from select animal species are added randomly to negative samples in an effort
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@Daoyu15 9-5/ @Daoyu15
to undermine the high correlation in the pre-10/03/2023 upload only with Homo Sapiens. This behavior is similar to them adding virus from an entirely unrelated lineage A source to A20 in an effort to “root the SARS-CoV-2 phylogenetic tree at the market” and
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@Daoyu15 9-6/ @Daoyu15
compromising the host composition (still no wildlife host present) not expected to see changes with mere “Viral amplicon sequencing”, another act that is done using a 26/03/2023 data release. 2: The “all correlations” graph merely indicate which stall the majority
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@Daoyu15 9-7/ @Daoyu15
of the positive samples are found in, which is the stall closest to the toilets. This is far more susceptible to spatial confounding factors such as sampler-linked contamination with the absence of meaningful spatial spread in Jan 12 compared to Jan 01. Note that
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@Daoyu15 9-8/ @Daoyu15
in both Jan 01 and Jan 12, the stall with the most positive samples out of all samples is the stall closest to the toilets, which you also see a few “positive stalls” with neither wildlife DNA nor human cases inside nearby in Jan 01, which are the respective stalls
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@Daoyu15 9-9/ @Daoyu15
that see the most direct sampler entries after the samplers have entered the market through the main entrance which is the toilet area.
This mean that “which species is most correlated in the stall” is a reasonable way to normalize out the spatial confounding
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@Daoyu15 9-10/ @Daoyu15
factor, making the analysis close to “which species shed the SARS-CoV-2 where it was found” and “which species is most correlated in the positive samples” asks this question explicitly while normalizing out all of the confounding factors. archive.md/CTP3i
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@Daoyu15 9-11/ @Daoyu15
archive.md/ETjzS archive.md/BWZJL archive.md/NeybM archive.md/2PM9Y archive.md/RirQ7 archive.md/FskYn archive.md/gvHfw archive.md/4cCHG
Failure of correlation within the positive samples crashed the Pearson
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@Daoyu15 9-12/ @Daoyu15
correlation within this stall, indicating that the select species merely landed on the different sections of the ground as the SARS-CoV-2 reads, whereas Homo Sapiens become the only mammals with consistent positive correlation over all 6 metrics.
Every stall
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@Daoyu15 9-13/ @Daoyu15
have a few unique species that is found in less than 4/7 stalls in the sample set, and more than half of these species are found on the ground. Some of the species such as Snakehead fish and pigs for example make no hosts for SARS-CoV-2, and merely coincided with
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@Daoyu15 9-14/ @Daoyu15
this criterion. Species like hedgehogs are explicitly proven to be non-susceptible to SARS-CoV-2 infection. These species at most landed on entirely different sections of the ground as SARS-CoV-2, explaining their lack of correlation with it inside the positive
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@Daoyu15 9-15/ @Daoyu15
samples and the crash of correlation inside the “wildlife stall A”.
The contamination source rubbed and trampled in Homo Sapiens, alongside several species of birds and fish that were found in the “志翔冻品商行” next to the toilets. Only Homo Sapiens is
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@Daoyu15 9-16/ @Daoyu15
susceptible to SARS-CoV-2 in this contamination source.
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@Daoyu15 10-1/ @Daoyu15
A sanity check—were there less pirates with higher temperatures where pirates are found or when in specific time? Neither. Were any of the “susceptible mammals” in the “wildlife stall” continued to correlate with SARS-CoV-2 when inside the stalls or inside the https://t.co/Ogfpf1jIoH
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@Daoyu15 10-2/ @Daoyu15
positive samples? Both crashed in correlation and they fall into zero or negative—the pirates are found on the wrong parts of the ocean at given temperatures just like the animals are found on the wrong sections of the ground when inside that “wildlife stall”.
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@Daoyu15 10引1-1/ @Daoyu15
Once inside “wildlife stall A”,
The only correlation crashed to Homo Sapiens. Others crashed to zero one metric or another. Same as in the positive samples. Ask “which species shed the SARS-CoV-2 where it is found” yield “Homo sapiens”. The “all samples” merely https://t.co/gRmBrps3fV
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@Daoyu15 10引1-2/ @Daoyu15
asks “which species is sold most uniquely in the stall closest to the toilets” with much of the animals being on the ground, entirely wrong sections, and a heavily confounded distribution pattern centered around the toilets same as W4-26-28 in Jan 01. https://t.co/lAhnPdR6Yf
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@Daoyu15 10引1-3/ @Daoyu15
archive.md/FskYn archive.md/gvHfw
Another oddity, is that for the entirety of the market, none of the personal items of vendors and none of the frequently directly handled objects from boxes to baskets to cashiers, were positive. This is because
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@Daoyu15 10引1-4/ @Daoyu15
SARS-CoV-2 RNA specifically is extremely unstable when on surfaces that are highly touched by a human—D614 especially because the Spike were too sparse to form a shield defending against invading RNAse 7. In fact, all of the positive samples in that “wildlife
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@Daoyu15 10引1-5/ @Daoyu15
stall A” and the majority of the positive samples in the market is below step height—they are contaminated by the toilets and archive.md/4cCHG archive.md/FskYn is the reason why the stall with the most positive samples out of all samples is the
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@Daoyu15 10引1-6/ @Daoyu15
stall closest to the toilets. In both Jan 01 and Jan 12.
Sampler contamination and cross-contamination. archive.md/LJzSO archive.md/VNr75 Never an infected vendor or animal. In fact, the samples in the market follows the rule which a positive