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Record W4413603132 · doi:10.1177/10406387251362461

Estimation of minimum centrifugation time of microhematocrit tubes to obtain accurate results of packed cell volume and total solids in donkeys, dogs, sheep, and cows

2025· article· en· W4413603132 on OpenAlexaff
Hélène Lardé, Juliette Bouillon, Ronan Whiston, Andrea Peda, Patricia M. Dowling, R Chapuis

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsUniversity of SaskatchewanCégep de RimouskiUniversité du Québec à Rimouski
FundersSchool of Veterinary Medicine, Ross University
KeywordsCentrifugationVeterinary medicineAnimal scienceDonkeyChromatographyBiologyAndrologyChemistryMedicine

Abstract

fetched live from OpenAlex

To date, the minimum centrifugation times of microhematocrit tubes of blood to generate accurate PCV and total solids (TS) results have not been validated in veterinary medicine. We collected blood samples from 44 donkeys, 43 dogs, 61 sheep, and 40 cattle. We centrifuged microhematocrit tubes for 1, 2, 3, 5, and 15 min in donkeys and dogs, and 1.5, 3, 5, 10, and 15 min in ruminants. We evaluated the agreements between PCV and TS values at each time of centrifugation with the reference values at 15 min using intra-class coefficients of correlation and linear regressions. Finally, we considered the symmetrical distribution of differences between results obtained at each time of centrifugation and the reference values. We found that microhematocrit tubes centrifuged for a minimum of 3 min in donkeys and dogs, 10 min in sheep, and 5 min in cattle gave PCV and TS results in agreement with the values obtained after 15 min of centrifugation. The centrifugation time for cattle was shorter than currently advised. However, because PCV values of all cattle and most donkeys enrolled were within RIs and because no polycythemic animals were included, validation of these times may be warranted.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.326
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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