Gastroenterology Endoscopy Nurses as Important Evaluators of Gastroenterology Fellow Performance
Bibliographic record
Abstract
Mitchell S. Cappell, PhD, MD, is Director of GI Fellowship Training Program and Chief of Gastroenterology & Hepatology, William Beaumont Hospital; and Professor of Medicine, Oakland University William Beaumont School of Medicine, Royal Oak, Michigan. Correspondence to: Mitchell S. Cappell, PhD, MD, Division of Gastroenterology & Hepatology, William Beaumont Hospital, MOB 602, 3535 W. Thirteen Mile Road, Royal Oak, MI 48073 ([email protected]). THE OFFICIAL JOURNAL OF THE SOCIETY OF GASTROENTEROLOGY NURSES AND ASSOCIATES, INC. AND THE CANADIAN SOCIETY OF GASTROENTEROLOGY NURSES AND ASSOCIATES DEDICATED TO THE SAFE AND EFFECTIVE PRACTICE OF GASTROENTEROLOGY AND ENDOSCOPY NURSING The author declares no conflicts of interest. Received May 01, 2013 Accepted November 03, 2013
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.199 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".