Prospective Evaluation of Colposcopic Features in Predicting Cervical Intraepithelial Neoplasia: Degree of Acetowhite Change Most Important
Bibliographic record
Abstract
OBJECTIVE.: To prospectively evaluate the contribution of three colposcopic features-degree of acetowhite change, blood vessel pattern, and lesion margin-to the diagnosis of cervical intraepithelial neoplasia. MATERIALS AND METHODS.: A total of 301 women, who participated in two randomized controlled trials and a cross-sectional study of human papillomavirus testing and who were referred to a regional colposcopy center, were studied. Women were examined by colposcopists, who prospectively scored all abnormal transformation zones using three features. The site with the highest score (the most abnormal site) was biopsied and histology reviewed by two pathologists. RESULTS.: In multivariate analysis, degree of acetowhite change was the only feature significantly associated with cervical intraepithelial neoplasia. CONCLUSIONS.: Grading lesion severity using degree of acetowhite change alone gave comparable results to grading using the three combined features.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".