Q-Probes Studies in Anatomic Pathology: Quality Improvement Through Targeted Benchmarking
Bibliographic record
Abstract
CONTEXT: The Q-Probes program is a peer-comparison quality assurance service offered by the College of American Pathologists that was created in 1989. OBJECTIVE: To establish national benchmarks around a specific quality metric at a specific point in time in anatomic pathology (AP). DESIGN: Q-Probes are based on a voluntary subscription for an individual study. Hospital-based laboratories in the United States, Canada, and 16 other countries have participated. Approximately one-third of all Q-Probes studies address AP metrics. Each Q-Probes study has a primary quality indicator and additional minor indicators. RESULTS: There have been 52 AP Q-Probes studies addressing process-, outcome-, and structure-related quality assurance issues. These Q-Probes studies often represented the first standardized national benchmark for specific metrics in the disciplines of cytopathology, surgical pathology, and autopsy pathology, and as such have been cited more than 1700 times in peer-reviewed literature. The AP Q-Probes studies that have been repeated over time demonstrate improvement in laboratory performance across an international spectrum. CONCLUSIONS: The Q-Probes program has produced important national benchmarks in AP, addressing preanalytic, analytic, and postanalytic factors in the disciplines of cytopathology, surgical pathology, and autopsy pathology. Q-Probes study data have been published, cited, and used in the creation of laboratory accreditation standards and other national guidelines.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".