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Record W3213942523 · doi:10.1071/rd21267

Female age and parity in horses: how and why does it matter?

2021· review· en· W3213942523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReproduction Fertility and Development · 2021
Typereview
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsReproductive technologyParity (physics)BiologyStem cell biologyReproductive immunologyGeneticsPhysicsPregnancy

Abstract

fetched live from OpenAlex

Although puberty can occur as early as 14-15months of age, depending on breed and use, the reproductive career of mares may continue to advanced ages. Once mares are used as broodmares, they will usually produce foals once a year until they become unfertile, and their productivity can be enhanced and/or prolonged through embryo technologies. There is a general consensus that old mares are less fertile, but maternal age and parity are confounding factors because nulliparous mares are usually younger and older mares are multiparous in most studies. This review shows that age critically affects cyclicity, folliculogenesis, oocyte and embryo quality as well as presence of oviductal masses and uterine tract function. Maternal parity has a non-linear effect. Primiparity has a major influence on placental and foal development, with smaller foals at the first gestation that remain smaller postnatally. After the first gestation, endometrial quality and uterine clearance capacities decline progressively with increasing parity and age, whilst placental and foal birthweight and milk production increase. These combined effects should be carefully balanced when breeding mares, in particular when choosing and caring for recipients and their foals.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.214
GPT teacher head0.411
Teacher spread0.198 · 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