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Record W4380148703 · doi:10.1016/j.cgh.2023.05.029

Standardizing Scoring Conventions for Crohn’s Disease Endoscopy: An International RAND/UCLA Appropriateness Study

2023· article· en· W4380148703 on OpenAlexaff
Reena Khanna, Christopher Ma, Malcolm Hogan, Guangyong Zou, Talat Bessissow, Brian Bressler, Jean‐Frédéric Colombel, Silvio Danese, Marco Daperno, James E. East, Lawrence Hookey, Edward V. Loftus, John WD McDonald, Remo Panaccione, Laurent Peyrin‐Biroulet, Matt Rutter, Bruce E. Sands, Séverine Vermeire, Julie Rémillard, Stefanie C. McFarlane, William J. Sandborn, Geert D’Haens, Brian G. Feagan, Vipul Jairath

Bibliographic record

VenueClinical Gastroenterology and Hepatology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsQueen's UniversitySt. Paul's HospitalMcGill University Health CentreUniversity of CalgaryWestern University
FundersNIHR Oxford Biomedical Research CentreNIHR Bristol Biomedical Research Centre
KeywordsMedicineAppropriateness criteriaCrohn's diseaseEndoscopyMEDLINECrohn diseaseMedical physicsGeneral surgeryInternal medicineDiseaseRadiology

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)0.052
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.112
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.377
Teacher spread0.330 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2023
Admission routes1
Has abstractno

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