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Record W3028629337 · doi:10.1021/acs.chas.0c00050

Let’s Disagree about Safety

2020· article· en· W3028629337 on OpenAlexaffabout
Mary Beth Mulcahy, John Holmes, Monona Rossol

Bibliographic record

VenueACS Chemical Health & Safety · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVEditorialNEXTLet's Disagree about SafetyMary Beth Mulcahy*Mary Beth MulcahySandia National Laboratories, Albuquerque, New Mexico 87123, United States*E-mail: [email protected]More by Mary Beth Mulcahy, John Holmes*John HolmesUniversity of Ottawa, Ottawa, Ontario K1N 6N5, Canada*E-mail: [email protected]More by John Holmes, and Monona Rossol*Monona RossolArts, Crafts & Theater Safety, New York, New York 10012, United States*E-mail: [email protected]More by Monona RossolCite this: ACS Chem. Health Saf. 2020, 27, 3, 135–138Publication Date (Web):May 26, 2020Publication History Published online26 May 2020Published inissue 26 May 2020https://pubs.acs.org/doi/10.1021/acs.chas.0c00050https://doi.org/10.1021/acs.chas.0c00050editorialACS PublicationsCopyright © 2020 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views3135Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (520 KB) Get e-AlertscloseSUBJECTS:Atmospheric chemistry,Liquids,Mercury,Safety,Students Get e-Alerts

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)0.019
metaresearch head score (Gemma)0.086
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 score0.100
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.086
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0090.011
Scholarly communication0.0120.016
Open science0.0030.007
Research integrity0.0300.041
Insufficient payload (model declined to judge)0.1000.076

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 head0.110
GPT teacher head0.391
Teacher spread0.281 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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