Effects of the temperature-humidity index on conception rates in Holstein heifers and cows receiving <i>in vitro</i>-produced Japanese Black cattle embryos
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".