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Record W4401503204 · doi:10.1016/j.animal.2024.101291

Editorial: The reporting of statistics in research articles is key to the understanding and reproducibility of good research in animal science

2024· editorial· en· W4401503204 on OpenAlexaff
Isabelle Ortigues Marty, Henrik Stryhn, Emmanuel Paquet, B. Ampe, Celeste Montoya, J. S. Fenlon

Bibliographic record

Venueanimal · 2024
Typeeditorial
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversité LavalUniversity of Prince Edward Island
Fundersnot available
KeywordsReproducibilityKey (lock)Data sciencePsychologyComputer scienceStatisticsInformation retrievalMathematics

Abstract

fetched live from OpenAlex

Editorial Material

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)0.034
metaresearch head score (Gemma)0.162
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.966
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.162
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0080.003
Science and technology studies0.0050.004
Scholarly communication0.0130.005
Open science0.0050.002
Research integrity0.0170.017
Insufficient payload (model declined to judge)0.0270.020

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 head0.598
GPT teacher head0.565
Teacher spread0.033 · 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.

Study designNot applicable
DomainReporting
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
Published2024
Admission routes1
Has abstractyes

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