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Record W4318573036 · doi:10.1262/jrd.2022-112

Effects of the temperature-humidity index on conception rates in Holstein heifers and cows receiving <i>in vitro</i>-produced Japanese Black cattle embryos

2023· article· en· W4318573036 on OpenAlexaff
Takamasa Nishisozu, Jaswant Singh, Akinori ABE, Kazuo Okamura, O. Dochi

Bibliographic record

VenueJournal of Reproduction and Development · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHeat indexAnimal scienceEmbryo transferRelative humidityDairy cattleEmbryoBiologyChemistryVeterinary medicineMedicineHeat stress

Abstract

fetched live from OpenAlex

We investigated the effect of the temperature-humidity index (THI) on the conception rate (CR) in Holstein heifers and cows receiving in vitro-produced (IVP) Japanese Black cattle fresh embryos. IVP embryos were transferred to Holstein heifers (n = 1,407) and cows (n = 3,189) on 245 commercial farms. The monthly average ambient temperature (AT) and THI ranged from 4.7 to 29°C and 41 to 81, respectively; both were the highest in August. The monthly CR ranged from 16.3% to 46.7% in cows and 23.8% to 74.1% in heifers. The CR of heifers was unaffected by THI, AT, or the month of embryo transfer. However, these parameters affected the CR of cows. The CR at THI values of 61-65 and 71-75 was greater than that at THI > 75, whereas other THI values had no effect. The CR at temperatures > 25°C was lower (P = 0.008) than that at temperatures of 15-20°C and 20-25°C. Moreover, the CR was lowest (P = 0.003) in July. THI and parity (P = 0.057 and P = 0.001, respectively) and AT and parity (P = 0.019 and P = 0.001, respectively) showed significant effects on CR; however, there was no interaction between these two factors. In conclusion, AT > 25°C and THI > 75 adversely affect the CR outcome in cows but not in heifers.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.238

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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 designBench or experimental
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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Reproduction and DevelopmentSame topicEffects of Environmental Stressors on LivestockFrench-language works237,207