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Record W2091410166 · doi:10.1530/jrf.0.1190293

Relationship between fertility in cattle and the number of inseminated spermatozoa

2000· article· en· W2091410166 on OpenAlexaff
J. Fearon, Paul Wegener

Bibliographic record

VenueReproduction · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsFertilitySemenBiologyBull semenSemen qualityAndrologyStatisticsMathematicsDemographyMedicineAnatomyCryopreservationEmbryoGeneticsPopulation

Abstract

fetched live from OpenAlex

Five different two-parameter models were fitted to published data from 30 studies to identify an approximate mathematical form of the relationship between fertility in cattle and the number of inseminated spermatozoa. In all cases, the first parameter defines the maximum attainable fertility, and the second scales the dose according to the percentage of the maximum attained. The best model was the hyperbolic dose-response curve used in pharmacology to analyse the effect of drugs. There is evidence that the semen of individual bulls differs in both parameters of the models and that therefore the viability of semen may be multidimensional. This might explain why measures of semen quality have hitherto been found to correlate poorly with fertility. The hypothesis that spermatozoa are subject to the law of mass action at the ovum predicts these and some other aspects of fertility, and indicates that heterospermic inseminations may provide an efficient way of estimating the parameters of semen.

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)0.010
metaresearch head score (Gemma)0.025
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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

Citations12
Published2000
Admission routes1
Has abstractyes

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