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Record W2811296422 · doi:10.1053/j.gastro.2018.05.038

World Endoscopy Organization Consensus Statements on Post-Colonoscopy and Post-Imaging Colorectal Cancer

2018· article· en· W2811296422 on OpenAlexaff
Matthew D. Rutter, Iosif Beintaris, Roland Valori, Han Mo Chiu, Douglas A. Corley, Míriam Cuatrecasas, Evelien Dekker, Anna Forsberg, Jola Gore-Booth, Ulrike Haug, Michał F. Kamiński, Takahisa Matsuda, Gerrit A. Meijer, Eva Morris, Andrew Plumb, Linda Rabeneck, Douglas J. Robertson, Robert E. Schoen, Harminder Singh, Jill Tinmouth, Graeme P. Young, Silvia Sanduleanu

Bibliographic record

VenueGastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of ManitobaCancer Care OntarioUniversity of Toronto
FundersMedical Research Council
KeywordsMedicineTerminologyColonoscopyColorectal cancerGrading (engineering)Delphi methodMedical physicsMEDLINEFamily medicineCancerInternal medicineComputer scienceArtificial intelligence

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)0.080
metaresearch head score (Gemma)0.147
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0800.147
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0060.004
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0040.004
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.300
Teacher spread0.290 · 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 designNot applicable
Domainnot available
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

Citations360
Published2018
Admission routes1
Has abstractno

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