The Implementation of Nongynecologic Reporting Systems in Cytopathology Laboratories Is Highly Variable: Analysis of Data From a 2020 Supplemental Survey of Participants in the College of American Pathologists Interlaboratory Comparison Program in Nongynecologic Cytology
Bibliographic record
Abstract
CONTEXT: In recent years, several reporting systems have been developed by national and international cytopathology organizations to standardize the evaluation of specific cytopathology specimen types. OBJECTIVE: To assess the current implementation rates, implementation methods, and barriers to implementation of commonly used nongynecologic reporting systems in cytopathology laboratories. DESIGN: Data were analyzed from a survey developed by the College of American Pathologists Cytopathology Committee and distributed to participants in the College of American Pathologists Nongynecologic Cytopathology Education Program mailing. RESULTS: Nongynecologic reporting systems with the highest rate of adoption were the Bethesda System for Reporting Thyroid Cytopathology, 2nd edition (74.1%; 552 of 745); the Paris System for Reporting Urinary Cytology (53.9%; 397 of 736); and the Milan System for Reporting Salivary Gland Cytopathology (29.1%; 200 of 688). The most common reason given for not adopting a reporting system was satisfaction with a laboratory's current system. Implementation varied among laboratories with regard to which stakeholders were involved in deciding to implement a system and the amount of education provided during the implementation process. CONCLUSIONS: The implementation of nongynecologic reporting systems in cytopathology laboratories was highly variable.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".