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Record W2133882079 · doi:10.1111/jlme.12253

What Will it Take to Address the Global Threat of Antibiotic Resistance?

2015· article· en· W2133882079 on OpenAlexaff
Steven J. Hoffman, Kevin Outterson

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsMinistry of Health and Long Term Care
Fundersnot available
KeywordsGeneral partnershipNorwegianFoundation (evidence)Antibiotic resistancePolitical scienceAction (physics)State (computer science)Resistance (ecology)Public administrationPublic healthEngineering ethicsPublic relationsMedicineLawAntibioticsEngineeringComputer scienceMicrobiologyBiologyNursing

Abstract

fetched live from OpenAlex

Of the many global health challenges facing the world today, only a small number require global collective action. Most health challenges can be fully addressed through action at local, regional or national levels. What kind of actions must be taken to address the global threat of antibiotic resistance (ABR)? What legal, political and economic tools might be needed to achieve this level of action? In March 2015 the Dag Hammarskjöld Foundation convened a workshop in Uppsala, Sweden to address these questions in partnership with the Global Strategy Lab, the Journal of Law, Medicine & Ethics (JLME), the Norwegian Institute of Public Health, and ReAct — Action on Antibiotic Resistance. Eleven concise articles were commissioned to explore whether ABR depended on global collective action, and if so, what tools could help states and non-state actors to achieve it.

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)0.038
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.056
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0050.018
Scholarly communication0.0170.025
Open science0.0030.005
Research integrity0.0260.016
Insufficient payload (model declined to judge)0.0060.002

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 head0.094
GPT teacher head0.362
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations46
Published2015
Admission routes1
Has abstractyes

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