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Record W156741044

Innovation and Best Practices in Endoscopy

2013· article· en· W156741044 on OpenAlexfundno aff
Christopher Teshima

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2013
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
FundersCanadian Association of Gastroenterology
KeywordsMedicinePaceEndoscopySpecialtyTherapeutic endoscopyClinical PracticeGeneral surgeryFamily medicineSurgery
DOInot available

Abstract

fetched live from OpenAlex

Advances in gastrointestinal (GI) endoscopy have played an important role in improving the diagnostic and therapeutic options for physicians treating patients with GI diseases. Indeed, the advent of endoscopy transformed the field of Gastroenterology and contributed significantly to its emergence as a specialty separate from Internal Medicine and General Surgery. As the pace of technological progress has quickened, innovation in GI endoscopy has only accelerated, expanding the tools available to the practicing gastroenterologist. However, it remains essential that physicians examine technology with a critical eye to ensure that new devices or techniques are truly an improvement for patient care, both in terms of efficacy and safety. In addition, it is important that existing practices are frequently examined and critically reevaluated in order to deliver clinical care at the highest level of quality. For this reason, clinical research is a necessary component of the modern practice of medicine, a maxim that holds true for GI endoscopy as much as for any other field.

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)0.049
metaresearch head score (Gemma)0.131
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: Methods · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.131
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.006
Science and technology studies0.0030.009
Scholarly communication0.0140.010
Open science0.0020.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0150.003

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 head0.051
GPT teacher head0.321
Teacher spread0.270 · 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
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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