Agreement in histologic assessments of the pituitary pars intermedia in aged horses
Bibliographic record
Abstract
OBJECTIVE: To evaluate concordance among veterinary pathologists in the assessment of histologic findings in the pars intermedia of pituitary gland sections from aged horses with mild signs suggestive of pituitary pars intermedia dysfunction (PPID). Sample Population-10 pituitary glands from aged horses. PROCEDURE: 7 pathologists were provided with signalment, clinical signs, and a single H&E-stained pituitary gland section from 10 aged horses with mild signs suggestive of PPID. Pathologists described histologic findings for each section and stated whether findings were consistent with PPID. Agreement among pathologists and with antemortem diagnostic test results was calculated. RESULTS: Overall, only fair agreement was found among the pathologists as to which horses had histologic findings consistent with disease (mean +/- SE kappa value, 0.34 +/- 0.069). Interpretation of individual sections varied, with minimal agreement (4 or 5/7 pathologists) for 5 of 10 sections evaluated. Postmortem assessment was in agreement with an antemortem endocrine diagnostic test result 79% of the time. CONCLUSIONS AND CLINICAL RELEVANCE: Validation of antemortem diagnostic testing for PPID in horses often relies on the results of postmortem histologic evaluation. The lack of consensus in histologic interpretation of pituitary glands from aged horses with mild clinical signs in our study indicates that postmortem histologic evaluation of pituitary glands is an inappropriate standard in validation of antemortem diagnostic tests for detection of early PPID. Caution should be used when interpreting diagnostic test results in horses in which early PPID is suspected.
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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 | 0.022 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".