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Record W4396787927 · doi:10.3168/jdsc.2024-0570

Hemoconcentration differs in neonatal dairy calves: Considerations for assessment of transfer of passive immunity

2024· article· en· W4396787927 on OpenAlexaff
T.A. Westhoff, R.A. Molano, M.E. Van Amburgh, Sabine Mann

Bibliographic record

VenueJDS Communications · 2024
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsSte. Anne's Hospital
FundersNew York Farm Viability Institute
KeywordsHemoconcentrationColostrumAnimal sciencePassive immunityMedicineHematocritChemistryInternal medicineBiologyImmunologyAntibody

Abstract

fetched live from OpenAlex

Assessing transfer of passive immunity (TPI) is a critical management strategy to evaluate colostrum management and feeding; however, variability in hemoconcentration or serum or plasma volume in calves might influence TPI assessment. The objectives of this study were to (1) describe the variability in hemoconcentration as well as TPI in Holstein calves in New York State and (2) describe the effect of adjusting total protein (TP) for the degree of hemoconcentration by applying a sample average proportion of plasma in blood (PP) on TPI assessment. Records of TP and PP from 703 Holstein calves 1 to 9 d of age from 19 commercial dairy farms were analyzed. The PP was determined by centrifugation of microhematocrit tubes and serum and plasma TP was determined by digital refractometry. Transfer of passive immunity was categorized using unadjusted TP (uTP) as excellent = ≥6.2, good = 5.8-6.1, fair = 5.1-5.7, and poor <5.1 g/dL. Individual calf TP concentrations were adjusted to the sample average PP and TPI categories were reassessed using the adjusted TP value (aTP). The sample mean ± SD (range) PP was 68.8% ± 5.8% (50.5% to 86.0%). The PP was lower on d 1 compared with d 7 of age. Using uTP to categorize TPI, 22 (3.1%) calves had poor, 113 (16.2%) calves had fair, 164 (23.6%) calves had good, and 397 (57.1%) calves had excellent TPI, respectively. After adjusting TP for hemoconcentration, TPI determined using aTP resulted in 52 (7.5%, +4.4 percentage points) calves in poor, 137 (19.7%, +3.5 percentage points) calves in fair, 122 (17.5%, -6.1 percentage points) calves in good, and 385 (55.3%, -1.8 percentage points) calves in excellent. The mean (range) proportion of calves with TPI determined using uTP by farm was 3.9% (0% to 16%) for poor, 19.0% (2% to 36%) for fair, 25.3% (10% to 42%) for good, 51.8% (26% to 83%) for excellent. When categorized using aTP, the proportion of calves by farm was 8.1% (0% to 21%) in poor, 20.5% (8% to 42%) in fair, 19.1% (6% to 33%) in good, and 52.4% (27% to 83%) in excellent TPI. In conclusion, PP was variable in calves during the time of TPI assessment and this variability should be considered when assessing TPI at the calf- or herd level.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.149
GPT teacher head0.432
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2024
Admission routes1
Has abstractyes

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