Comparison of hysteroscopic and hysterectomy findings to assess the diagnostic \naccuracy of office hysteroscopy in tamoxifen-treated patients with breast cancer
Bibliographic record
Abstract
Study Objective. To assess the diagnostic accuracy of office hysteroscopy by comparing hysteroscopic findings with histologic \nfindings on hysterectomy specimens in postmenopausal women with breast cancer treated with tamoxifen. \nDesign. Retrospective clinical study (Canadian Task Force classification II-2). \nSetting. University-affiliated hospital. \nPatients. Thirty-three women. \nIntervention. Record review. \nMeasurements and Main Results. Compared with histologic diagnoses of uteri, hysteroscopic findings showed diagnostic sensitivity \nof 97%, specificity of 100%, positive predictive value of 100% and negative predictive value of 96%. The diagnostic \naccuracy of hysteroscopy is the same in patients taking tamoxifen as in the general population. \nConclusion. Hysteroscopy is a powerful method for diagnosing endometrial disease because it provides a direct view of the \nuterine cavity, reveals focal lesions, and enables targeted biopsies to be performed at the same time.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".