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Record W1596457615 · doi:10.1111/bph.12856

Experimental design and analysis and their reporting: new guidance for publication in <scp>BJP</scp>

2015· editorial· en· W1596457615 on OpenAlexaff
Michael J. Curtis, Richard A. Bond, Domenico Spina, Amrita Ahluwalia, S P H Alexander, Mark A. Giembycz, Annette Gilchrist, Daniël Hoyer, Paul A. Insel, Angelo A. Izzo, Andrew J. Lawrence, David J. MacEwan, Lawrence Moon, A.H. Weston, J.C. McGrath

Bibliographic record

VenueBritish Journal of Pharmacology · 2015
Typeeditorial
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCanadian Journal of Communication (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsLibrary scienceArtComputer science

Abstract

fetched live from OpenAlex

Linked Editorials This Editorial is part of a series. To view the other Editorials in this series, visit: http://onlinelibrary.wiley.com/doi/10.1111/bph.12956/abstract ; http://onlinelibrary.wiley.com/doi/10.1111/bph.12954/abstract ; http://onlinelibrary.wiley.com/doi/10.1111/bph.12955/abstract and http://onlinelibrary.wiley.com/doi/10.1111/bph.13112/abstract

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)0.251
metaresearch head score (Gemma)0.633
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.749
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2510.633
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0170.016
Science and technology studies0.0030.005
Scholarly communication0.0140.008
Open science0.0080.005
Research integrity0.0160.021
Insufficient payload (model declined to judge)0.1260.128

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 head0.498
GPT teacher head0.527
Teacher spread0.029 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations1,025
Published2015
Admission routes1
Has abstractyes

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