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Record W3010808398 · doi:10.1503/cmaj.200428

Working together to contain and manage COVID-19

2020· letter· en· W3010808398 on OpenAlexvenueaboutno aff
Andreas Laupacis

Bibliographic record

VenueCanadian Medical Association Journal · 2020
Typeletter
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSocial distanceClosing (real estate)2019-20 coronavirus outbreakOutbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Public healthCoronavirusCategorizationPolitical sciencePublic relationsPublic administrationEconomic growthVirologyDiseaseMedicineInfectious disease (medical specialty)Computer scienceNursingLawEconomics

Abstract

fetched live from OpenAlex

Canada’s federal and provincial governments have taken unprecedented measures to promote social distancing in the wake of the World Health Organization’s categorization of the coronavirus disease 2019 (COVID-19) outbreak as a global pandemic. Closing schools, banning large public gatherings and

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.749
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0320.007
Scholarly communication0.0060.005
Open science0.0030.006
Research integrity0.0380.064
Insufficient payload (model declined to judge)0.0200.009

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 head0.048
GPT teacher head0.361
Teacher spread0.314 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations30
Published2020
Admission routes2
Has abstractyes

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