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<scp>ASVCP</scp>quality assurance guidelines: control of preanalytical, analytical, and postanalytical factors for urinalysis, cytology, and clinical chemistry in veterinary laboratories

2012· article· en· W2156696852 on OpenAlexaff
Rebekah G. Gunn‐Christie, Bente Flatland, Kristen R. Friedrichs, Balázs Szladovits, Kendal E. Harr, Kristiina Ruotsalo, Joyce S. Knoll, Heather L. Wamsley

Bibliographic record

VenueVeterinary Clinical Pathology · 2012
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsUrinalysisQuality assuranceMedical laboratoryMedical physicsMedicineStandardizationExternal quality assessmentPathologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.073
metaresearch head score (Gemma)0.133
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.073
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.133
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.006
Science and technology studies0.0040.004
Scholarly communication0.0100.004
Open science0.0090.004
Research integrity0.0110.009
Insufficient payload (model declined to judge)0.0280.053

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.

Opus teacher head0.217
GPT teacher head0.504
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations79
Published2012
Admission routes1
Has abstractyes

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