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Record W2938670512 · doi:10.1111/iej.13125

Preferred Reporting Items for Animal Studies in Endodontology: a development protocol

2019· review· en· W2938670512 on OpenAlexaff
Venkateshbabu Nagendrababu, Anil Kishen, Peter E. Murray, M. H. Nekoofar, José Antônio Poli de Figueiredo, E. Priya, Jayakumar Jayaraman, Shaju Jacob Pulikkotil, P. M. H. Dummer

Bibliographic record

VenueInternational Endodontic Journal · 2019
Typereview
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProtocol (science)Animal welfareMedicineCLARITYAnimal testingDelphi methodQuality (philosophy)Alternative medicinePathologyComputer science

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.174
metaresearch head score (Gemma)0.231
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.826
Threshold uncertainty score0.919

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1740.231
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0080.005
Bibliometrics0.0110.008
Science and technology studies0.0060.006
Scholarly communication0.0110.007
Open science0.0080.007
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.1590.097

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 head0.794
GPT teacher head0.619
Teacher spread0.175 · 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
GenreProtocol

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

Citations19
Published2019
Admission routes1
Has abstractyes

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