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Record W4391880796 · doi:10.1017/s0022029924000050

Concentrations of antimicrobial components in milk at dry off and postpartum and their relationships to new high somatic cell counts at quarter level in dairy cows

2024· article· en· W4391880796 on OpenAlexaboutno aff
Naoki Suzuki, Rika Harada, Yusaku Tsugami, Takahiro Nii, Naoki Isobe

Bibliographic record

VenueJournal of Dairy Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Somatic cellSomatic cell countAnimal scienceAntimicrobialDairy industryDairy cattleBiologyFood scienceMicrobiologyGeographyIce calvingLactationPregnancyGenetics

Abstract

fetched live from OpenAlex

We investigated the antimicrobial components in cow milk at dry off and postpartum and their contribution in preventing new high SCC at quarter level. Milk samples from 72 quarters of 19 lactating cows were collected at last milking before dry off and at 7 d after parturition. Milk yield of each cow was recorded and SCC, IgG, IgA, lactoferrin, lingual antimicrobial peptide (LAP), and S100A7 concentrations in each quarter milk sample were measured. The postpartum milk yield was significantly higher than that at dry off. The IgG, IgA and lactoferrin concentrations in milk at dry off were significantly higher than those at postpartum, whereas the LAP concentration was lower. Quarters with SCC < 300 000 cells/ml at both dry off and postpartum were classified as persistent low SCC (PL) whereas those that rose above that same threshold postpartum were classified as new high SCC (NH). At dry off, IgG and LAP concentrations in milk were significantly higher in PL than in NH. These results suggest that high LAP concentrations during the dry period may contribute toward the prevention of new high SCC.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.144
GPT teacher head0.314
Teacher spread0.170 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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