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Record W2946379042 · doi:10.1111/jvim.15519

Modified stall-side crossmatch for transfusions in horses

2019· article· en· W2946379042 on OpenAlexaff
Pauline Casenave, Mathilde Leclère, Guy Beauchamp, Marie‐Claude Blais

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsMedicineAntibodyChromatographyImmunologyChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: After-hours or out-of-clinic crossmatches are often limited by the lack of access to specialized material and technical expertise. HYPOTHESIS/OBJECTIVES: The goal was to adapt a stall-side crossmatch test for pretransfusion evaluation in horses. ANIMALS: Twelve healthy mares (plasma and blood donors, teaching mares). METHODS: In a prospective study, blood from 12 mares was used to compare the results of 132 crossmatches performed with a rapid gel assay to crossmatches performed with a microgel column assay, and with predicted compatibilities based on blood types and detection of antibodies at a reference laboratory (microplate assay). The rapid gel assay protocol for dogs was adapted to decrease the formation of rouleaux that initially precluded equine erythrocytes migration through the gel. RESULTS: There was a good agreement between the rapid gel assay and the microgel assay as well as with the predicted compatibilities (κ > .6 for both). Agreement was higher between the microgel assay and the predicted compatibilities (κ = .8). The rapid gel assay failed to detect 6 predicted Aa incompatibilities (agglutinins-related), 3 of which were also not detected with the microgel assay. CONCLUSIONS AND CLINICAL IMPORTANCE: Based on these results, the modified rapid gel assay could be useful in settings when access to the microgel assay is not available. Discrepancies between both gel techniques and predicted compatibilities were most often low-grade agglutination, which warrants further investigation to assess their clinical importance.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.367
Teacher spread0.306 · 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 designObservational
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

Citations18
Published2019
Admission routes1
Has abstractyes

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