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Record W4389903933 · doi:10.1016/j.cgh.2023.12.007

Interim Analysis of a Trial Evaluating the Utility of Non-Targeted Biopsies for Colorectal Neoplasia Detection in Inflammatory Bowel Disease

2023· article· en· W4389903933 on OpenAlexafffund
Sanjay K. Murthy, Çharles N. Bernstein, Geoffrey C. Nguyen, Vipul Jairath, Robert H. Riddell, Dean Fergusson, James Conner, Tim Ramsay, Jane Castelli, Faria Ahmed, Neeraj Narula, Talat Bessissow, Brian Bressler, Mark Borgaonkar, Jennifer M. Jones, Dustin Loomes, Frank Hoentjen, Daniel C. Baumgart, Petros Zezos, Jennifer Ramsay

Bibliographic record

VenueClinical Gastroenterology and Hepatology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsLondon Health Sciences CentreWestern UniversityOttawa Public HealthUniversity of TorontoMount Sinai HospitalOttawa HospitalUniversity of ManitobaInstitute for Clinical Evaluative SciencesUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineInflammatory bowel diseaseInterimInterim analysisColorectal cancerInternal medicineDiseaseGastroenterologyClinical trialCancer

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.366
Teacher spread0.331 · 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 designNon-randomized trial
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

Citations3
Published2023
Admission routes2
Has abstractno

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