Motion – Screening and Surveillance of Barrett’s Epithelium Is Practical and Cost Effective: Arguments against the Motion
Bibliographic record
Abstract
The issue of whether to screen individuals for Barrett's esophagus (BE) to prevent esophageal adenocarcinoma (EAC) is highly controversial. Important considerations are that BE is not highly prevalent in the general population and that not many patients with BE develop or die from EAC. Studies that suggest an improved prognosis from surveillance programs are susceptible to lead-time bias. Most of the principles for effective screening, as outlined by the World Health Organization, are not met by endoscopic screening and surveillance protocols. The diagnosis of BE (and dysplasia) is often unclear. Most patients with BE are not identified by screening, and few deaths would be prevented by surveillance. A decision analysis found that the most cost effective screening protocol would be every five years, but the costs associated with prolongation of life are very high, even if a group at high risk for EAC could be identified.
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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 | 0.038 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".