Argonne National Lab used five of the world's most powerful supercomputers to narrow a billion molecules to a few thousand in the search for Covid-19 antivirals.
Mostly true True in substance, wrong in a detail.
Factual: Statements about the present or the past, checked against the record: did they hold up?
Said for an organisation they lead or work for; it counts on both records.
What would count as true or false
True: credible reports confirm that by May 2020 Argonne National Laboratory used about five of the world's top supercomputers to screen about a billion molecules down to a few thousand candidates for Covid-19 treatment. Mostly true: the screening happened as described, with a minor discrepancy in the number of supercomputers, the molecule counts, or their ranking. Mixed: Argonne did large-scale screening, but key figures differ substantially (e.g., millions screened rather than a billion). Mostly false: the work was done by others, or was only planned, with Argonne playing a minor role. False: no such screening by Argonne took place.
Set before the research began.
Evidence (4)
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E1 Argonne's COVID-19 modeling combines physics and artificial intelligence Federal Laboratory Consortium (federallabs.org) · 27 April 2020
“Their deep-learning plus physics-based method is allowing them to reduce 1 billion possible molecules to 250 million; 250 million to 6 million; and 6 million to a few thousand.”
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E2 Argonne's COVID-19 modeling combines physics and artificial intelligence Federal Laboratory Consortium (federallabs.org) · 27 April 2020
“The project is using several of the most powerful supercomputers on the planet to run millions of simulations”
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E3 Argonne Scientists Enlisted in Fight Against COVID-19 WTTW News · 16 April 2020
“The supercomputer is then able to narrow the list of potential treatments from “billions of compounds” down to “maybe a thousand” that scientists can then test in a lab.”
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E4 Argonne science combats COVID-19 on four fronts Federal Laboratory Consortium (federallabs.org) · 3 April 2020
“Argonne scientists comb through databases that hold information on some 10 billion molecules.”
Reasoning
E1, an April 2020 federal lab news item, describes the Argonne-led team reducing 1 billion possible molecules in stages to a few thousand, which matches the claimed funnel. E2 says the project used 'several of the most powerful supercomputers on the planet' but does not confirm the specific number five. E3 and E4 support large-scale Argonne molecular screening with somewhat different molecule counts. The core claim is confirmed, but the exact count of five supercomputers is not verified, so the verdict is mostly true rather than true.
Cite this claim
Ray Kurzweil, “Argonne National Lab used five of the world's most powerful supercomputers to narrow a billion molecules to a few thousand in the search for Covid-19 antivirals.” (said May 2020). Verdict: mostly true. Reliability API, claim c_4db8adb43136, method 0.1.0+28da144b, dataset release v1.1.2. https://epistacklabs.com/claims/c_4db8adb43136
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
More factual claims by Ray Kurzweil
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Mostly false
“Right now, you’re getting back about four months a year.”
Currently scientific progress gives back about four months of life expectancy per year.
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Mostly false
“And then AlphaFold 2 in 2022 went through 200 million proteins and got the shape exactly correct, and that’s going to help come up with new medications.”
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Resolved true
“As of two or three years ago, we had gone through 170,000 proteins.”
As of two or three years ago, 170,000 proteins had been worked through by people.
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Mixed
“The current method for testing these few treatments is to organize a few hundred human subjects and then test them over about a year and a half, at a cost of hundreds of millions of dollars.”
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Mostly true
“Very often, the first several solutions tested on humans are not ideal and lead to other solutions that also take a few years to develop and test.”
Verdicts are made automatically; how verdicts are made.