Suggested Guidelines for Immunohistochemical Techniques in Veterinary Diagnostic Laboratories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This document is the consensus of the American Association of Veterinary Laboratory Diagnosticians (AAVLD) Subcommittee on Standardization of Immunohistochemistry on a set of guidelines for immunohistochemistry (IHC) testing in veterinary laboratories. Immunohistochemistry is a powerful ancillary methodology frequently used in many veterinary laboratories for both diagnostic and research purposes. However, neither standardization nor validation of IHC tests has been completely achieved in veterinary medicine. This document addresses both issues. Topics covered include antibody selection, fixation, antigen retrieval, antibody incubation, antibody dilutions, tissue and reagent controls, buffers, and detection systems. The validation of an IHC test is addressed for both infectious diseases and neoplastic processes. In addition, storage and handling of IHC reagents, interpretation, quality control and assurance, and troubleshooting are also discussed. Proper standardization and validation of IHC will improve the quality of diagnostics in veterinary laboratories.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it