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Record W4417498285 · doi:10.2471/blt.25.294438

Social science contributions to the global action plan on antimicrobial resistance

2025· article· en· W4417498285 on OpenAlexaff
Mathieu J. P. Poirier, Isaac Weldon, Clare Chandler, Daniela Corno, Laura Valtere, Pedro Henrique Dias Batista, Daniel Carelli, Geneviève Boily-Larouche, Sonia Lewycka, Fiona Emdin, Kathleen Liddell, Timo Minssen, Ilaria Natali, Susan Nayiga, Iruka N. Okeke, Emmanuel Olamijuwon, Kevin Outterson, Julianne Piper, Kayla Strong, Jarnail Singh Thakur, Kednapa Thavorn, Maarten van der Heijden, A. M. Viens, Mary Wiktorowicz, Steven J. Hoffman

Bibliographic record

VenueBulletin of the World Health Organization · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsOttawa HospitalCentre for Global Health ResearchSimon Fraser UniversityYork University
FundersNovo Nordisk FondenNovo NordiskWellcome Trust
KeywordsAction planAction (physics)Plan (archaeology)Antibiotic resistanceResistance (ecology)Global health

Abstract

fetched live from OpenAlex

Funding: This work is supported by the Social Sciences & Humanities Research Council [#895-2022-1015] and the Wellcome Trust [222422/Z/21/Z]. This work was also supported, in part, by a Novo Nordisk Foundation Grant for a scientifically independent International-Collaborative Bioscience Innovation & Law Programme (Inter-CeBIL) programme (#NNF23SA0087056 & #NNF17SA0027784).

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.009
GPT teacher head0.299
Teacher spread0.290 · 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.

Study designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

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