MétaCan
Menu
Back to cohort
Record W4387747845 · doi:10.1016/j.accpm.2023.101314

Comments on: Reducing the Risks of Nuclear War—The Role of Health Professionals

2023· editorial· en· W4387747845 on OpenAlexaff
Jean‐Yves Lefrant, Dan Benhamou, Marc-Olivier Fischer, Romain Pirracchio, Bernard Allaouchiche, Sophie Bastide, Matthieu Biais, Alice Blet, Lionel Bouvet, Olivier Brissaud, Sorin J. Brull, Xavier Capdevila, Nicola Groes Clausen, Philippe Cuvillon, Christophe Dadure, Jean David, Victoria Eley, Patrice Forget, Tomoko Fujii, Anne Godiér, PD Gopalan, Pierre‐Grégoire Guinot, Ahmed Hasanin, Olivier Joannès-Boyau, Sébastien Kerever, Éric Kipnis, Ruth Landau, Morgan Le Guen, Matthieu Legrand, Emmanuel Lorne, F. Mercier, Nicolas Mongardon, Sheila Nainan Myatra, Armelle Nicolas-Robin, Mark Peters, Hervé Quintard, Jordi Rello, Philippe Richebé, Jason A. Roberts, Filippo Sanfilippo, Antoine Schneider, Mircea T. Sofonea, Miriam M. Treggiari, Francis Veyckemans, Britta S. von Ungern‐Sternberg, Ahed Zeidan, Laurent Zieleskiewicz, Marzena Zielińska, Alexandre Milman, Antoine Roquilly

Bibliographic record

VenueAnaesthesia Critical Care & Pain Medicine · 2023
Typeeditorial
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineHealth professionalsIntensive care medicineHealth careLaw

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.015
metaresearch head score (Gemma)0.070
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 score0.069
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.070
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0030.003
Science and technology studies0.0080.005
Scholarly communication0.0100.006
Open science0.0070.003
Research integrity0.0690.052
Insufficient payload (model declined to judge)0.0170.013

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 head0.056
GPT teacher head0.429
Teacher spread0.373 · 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 abstractno

Explore more

Same venueAnaesthesia Critical Care & Pain MedicineSame topicNuclear Issues and DefenseFrench-language works237,207