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Record W4386099101 · doi:10.1136/bmj.p1946

We need a universally endorsed definition of a pandemic for the Pandemic Accord to be effective

2023· editorial· en· W4386099101 on OpenAlexaff
Noor Shakfeh, Fifa Rahman, Katri Bertram

Bibliographic record

VenueBMJ · 2023
Typeeditorial
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsImpact
Fundersnot available
KeywordsPandemicScope (computer science)NegotiationCoronavirus disease 2019 (COVID-19)Focus (optics)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Computer scienceInfluenza pandemicPolitical scienceMedicineVirologyLawDiseaseInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

For the Pandemic Accord to be effective, member states must urgently focus negotiations to define its scope, including its definition of “pandemic,” and ensure the definition avoids the pitfalls of past mistakes, argue Noor Shakfeh, Fifa Rahman, and Katri Bertram

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)0.039
metaresearch head score (Gemma)0.139
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.046
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.139
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0060.003
Science and technology studies0.0090.010
Scholarly communication0.0200.012
Open science0.0080.003
Research integrity0.0460.063
Insufficient payload (model declined to judge)0.0100.012

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 head0.379
Teacher spread0.317 · 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
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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