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Record W2505167779

Effect of Season on Pregnancy Rates, Milk Progesterone, and Milk Melatonin Profiles in Water Buffalo Reared in Canada

2016· dissertation· en· W2505167779 on OpenAlexaboutno aff
Anuja Dharap

Bibliographic record

VenueThe Atrium (University of Guelph) · 2016
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsMelatoninAnimal sciencePregnancyBiologyWater buffaloAndrologyEndocrinologyMedicineVeterinary medicineGenetics
DOInot available

Abstract

fetched live from OpenAlex

Having recently been introduced to Canada, water buffalo products have a growing market demand. While water buffaloes are seasonal breeders in some environments, the impact of season on estrus patterns in Canada is unknown. Pregnancy rates for buffaloes artificially inseminated in different seasons following synchronization or natural estrus were calculated. Milk samples were used to determine variation in progesterone and melatonin during summer (long days) and winter (short days). Milk was collected from randomly selected buffaloes and hormones were measured via enzyme-linked immunosorbent assays (ELISA). Spring and summer pregnancy rates were lower than in fall and winter. Spring and summer samples showed low progesterone concentrations with abrupt rise and fall. Fall and winter samples showed high progesterone with prolonged peaks and 20-22-day estrous cycles. No significant trend was observed in melatonin levels. Results indicate breeding seasons in Canada are fall and winter while low breeding seasons are spring and summer.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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