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Record W3132221372 · doi:10.1038/s41591-021-01281-1

A Neanderthal OAS1 isoform protects individuals of European ancestry against COVID-19 susceptibility and severity

2021· article· en· W3132221372 on OpenAlexafffund
Sirui Zhou, Guillaume Butler‐Laporte, Tomoko Nakanishi, David Morrison, Jonathan Afilalo, Marc Afilalo, Lætitia Laurent, Maik Pietzner, Nicola D. Kerrison, Kaiqiong Zhao, Elsa Brunet‐Ratnasingham, Danielle Henry, Nofar Kimchi, Zaman Afrasiabi, Nardin Rezk, Meriem Bouab, Louis Petitjean, Charlotte Guzman, Xiaoqing Xue, Chris Tselios, Branka Vulesevic, Olumide Adeleye, Tala Abdullah, Noor Almamlouk, Yiheng Chen, Michaël Chassé, Madéleine Durand, Clare Paterson, Johan Normark, Robert Frithiof, Miklós Lipcsey, Michael Hultström, Celia M.T. Greenwood, Hugo Zeberg, Claudia Langenberg, Elin Thysell, Michaël Pollak, Vincent Mooser, Vincenzo Forgetta, Daniel E. Kaufmann, J. Brent Richards

Bibliographic record

VenueNature Medicine · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcGill Genome CentreMcGill University Health CentreUniversité de MontréalCentre Hospitalier de l’Université de MontréalMcGill UniversityJewish General Hospital
FundersMedical Research CouncilFonds de Recherche du Québec - SantéNational Institutes of HealthEuropean CommissionKing's College LondonCanadian Institutes of Health ResearchCompute CanadaScience for Life LaboratoryVetenskapsrådetJapan Society for the Promotion of ScienceCancer Research UKMcGill University Health CentrePublic Health Agency of CanadaMcGill UniversityJewish General HospitalNational Institute for Health and Care ResearchPublic Health AgencyamfAR, The Foundation for AIDS Research
KeywordsImmunologyConfoundingOdds ratioBiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.320
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations301
Published2021
Admission routes2
Has abstractno

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