ERCP‐directed brush cytology prepared by the Thinprep<sup>®</sup> method: test performance and morphology of 149 cases
Bibliographic record
Abstract
Conventionally prepared endobiliary brushings are moderately (42%) sensitive and highly (98%) specific in detecting malignancy. The performance and morphological features of brushings prepared by Thinprep, a liquid-based method are mostly unknown. All brushings were retrieved from the laboratory files. Disease was classified as benign or malignant by linkage with the provincial cancer registry and sensitivity, specificity, positive (PPV) and negative predictive values (NPV) calculated. True positives and negatives were reviewed and predictive morphological features analysed by regression tree analysis. Out of 149 brushings, 55 (37%) were positive and 94 (63%) negative. Malignancy was identified in 86 (58%) and benign disease in 63 (42%) of the cases. The sensitivity was 51%, specificity 83%, PPV 80% and NPV 55%. Absolute discriminants of positive and negative brushings were not found, but nuclear cytoplasmic ratio was a useful feature. The performance of Thinprep-prepared brushings from this anatomical site was comparable with conventional preparations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".