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Record W2149833791 · doi:10.1186/s12916-015-0321-8

Erratum: the National Institutes of Health and guidance for reporting preclinical research

2015· erratum· en· W2149833791 on OpenAlexaff
David Moher, Marc T. Avey, Gerd Antes, Douglas G. Altman

Bibliographic record

VenueBMC Medicine · 2015
Typeerratum
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePreclinical researchMedical physics

Abstract

fetched live from OpenAlex

This is an Erratum to BMC Medicine 2015, 13:34, highlighting a corrected references list. Please see related article: http://www.biomedcentral.com/1741-7015/13/34.

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)0.025
metaresearch head score (Gemma)0.149
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: Other · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.149
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.005
Science and technology studies0.0030.003
Scholarly communication0.0080.005
Open science0.0050.003
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0960.105

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 head0.826
GPT teacher head0.628
Teacher spread0.198 · 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
GenreOther

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

Citations44
Published2015
Admission routes1
Has abstractyes

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