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Record W4389833954 · doi:10.1002/9781119525127.ch7

Colonoscopy and Flexible Sigmoidoscopy

2023· other· en· W4389833954 on OpenAlexaff
Catharine M. Walsh MD MEd PhD FRCPC, Ahmir Ahmad MBBS BSc MRCP, Brian P. Saunders MD FRCP FRCS, Jonathan Cohen MD FASGE FACG, Peter B. Cotton MD FRCP FRCS, Christopher B. Williams BM FRCP FRCS, Stephen Preston

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsColonoscopySigmoidoscopyBowel preparationMedicineGeneral surgeryColorectal cancerMedical physicsRadiologySurgeryComputer scienceInternal medicineCancer

Abstract

fetched live from OpenAlex

The place of colonoscopy in clinical practice depends on local circumstances and available endoscopic expertise. Colonoscopy and flexible sigmoidoscopy achieve more than radiological imaging techniques do because of their greater accuracy and histologic and therapeutic capabilities. Obtaining full informed patient consent is essential before an invasive procedure such as colonoscopy, with its potential for adverse events. Most patients can manage bowel preparation at home, arrive for colonoscopy, and walk out shortly afterwards. Most skilled endoscopists favor the one-person “single-handed” approach, in which the colonoscopist manages the angulation controls and valves with one hand and inserts or twists the shaft with the other. However, there are many who use two hands on the angulation controls and a few experts who work successfully with the “two-person” method, using an assistant to manipulate the shaft.

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)0.001
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0330.011

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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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