<scp>ASVCP</scp>quality assurance guidelines: control of preanalytical, analytical, and postanalytical factors for urinalysis, cytology, and clinical chemistry in veterinary laboratories
Bibliographic record
Abstract
In December 2009, the American Society for Veterinary Clinical Pathology (ASVCP) Quality Assurance and Laboratory Standards committee published the updated and peer-reviewed ASVCP Quality Assurance Guidelines on the Society's website. These guidelines are intended for use by veterinary diagnostic laboratories and veterinary research laboratories that are not covered by the US Food and Drug Administration Good Laboratory Practice standards (Code of Federal Regulations Title 21, Chapter 58). The guidelines have been divided into 3 reports: (1) general analytical factors for veterinary laboratory performance and comparisons; (2) hematology, hemostasis, and crossmatching; and (3) clinical chemistry, cytology, and urinalysis. This particular report is one of 3 reports and documents recommendations for control of preanalytical, analytical, and postanalytical factors related to urinalysis, cytology, and clinical chemistry in veterinary laboratories and is adapted from sections 1.1 and 2.2 (clinical chemistry), 1.3 and 2.5 (urinalysis), 1.4 and 2.6 (cytology), and 3 (postanalytical factors important in veterinary clinical pathology) of these guidelines. These guidelines are not intended to be all-inclusive; rather, they provide minimal guidelines for quality assurance and quality control for veterinary laboratory testing and a basis for laboratories to assess their current practices, determine areas for improvement, and guide continuing professional development and education efforts.
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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 | 0.073 | 0.133 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.028 | 0.053 |
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".