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Record W3093510417 · doi:10.1503/cmaj.200648-f

Traitement des patients atteints d’une forme modérée ou grave de maladie à coronavirus 2019: Ligne directrice fondée sur des données probantes

2020· article· fr· W3093510417 on OpenAlexaffvenue
Zhikang Ye, Bram Rochwerg, Ying Wang, Neill K. J. Adhikari, Srinivas Murthy, François Lamontagne, Robert Fowler, Haibo Qiu, Wei Li, Ling Sang, Mark Loeb, Ning Shen, Minhua Huang, Zhaonan Jiang, Yaseen M. Arabi, Luis Enrique Colunga‐Lozano, Li Jiang, Younsuck Koh, Dong Liu, Fang Liu, Jason Phua, Aizong Shen, Tianyi Huo, Bin Du, Suodi Zhai, Gordon Guyatt

Bibliographic record

VenueCanadian Medical Association Journal · 2020
Typearticle
Languagefr
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsMcMaster UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)HumanitiesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakPolitical scienceCoronavirusArtMedicineVirology

Abstract

fetched live from OpenAlex

POINTS CLÉS C’est le 11 mars 2020 que l’Organisation mondiale de la santé (OMS) a officiellement déclaré l’état de pandémie relativement à la flambée de maladie à coronavirus 2019 (COVID-19). La propagation de la COVID-19 à l’échelle mondiale représente une importante menace pour

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.062
GPT teacher head0.337
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2020
Admission routes2
Has abstractyes

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