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Record W2823094223 · doi:10.1136/vr.104932

Effect of blood ionised calcium concentration at calving on fertility outcomes in dairy cattle

2018· article· en· W2823094223 on OpenAlexaboutno aff
Philippa Jane Mahen, Helen Williams, Robert F. Smith, David Hugh Grove-White

Bibliographic record

VenueVeterinary Record · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
FundersForFarmersUniversity of LiverpoolBoehringer Ingelheim
KeywordsIce calvingEndometritisFertilityCalciumMilk feverMedicineHypocalcaemiaSubclinical infectionAnimal scienceHerdDairy cattlePhysiologyBiologyPregnancyLactationInternal medicineEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

Clinical and subclinical hypocalcaemia are common in dairy cows, yet evidence in the literature assessing their impact on fertility is inconsistent. The aim of this prospective cohort study was to examine associations between blood ionised calcium concentration at calving and fertility outcomes in dairy cattle. Blood samples were taken from 137 Holstein cows from four commercial dairy herds within 24 hours of calving and analysed for blood ionised calcium using an Epocal Point of Care Analyser (Epocal, Ottawa, Canada). Data collected from routine veterinary fertility examinations and herd records were used to investigate the association of ionised calcium with the outcomes: time to first service, time to conception and endometritis. There were significant negative associations between blood ionised calcium concentration and time to first service (HR 1.33, P=0.001) and blood ionised calcium concentration and time to conception (HR 1.16, P=0.04). There was no significant association between blood ionised calcium concentration and endometritis. The results of this study imply that management policies that minimise the reduction in blood ionised calcium concentration in the periparturient dairy cow are likely to improve reproductive outcomes and should be considered as part of the multifactorial approach to optimising dairy cow fertility.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.201

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 head0.040
GPT teacher head0.297
Teacher spread0.257 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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