Daily lying behavior of lactating Holstein cows during an estrus synchronization protocol and its associations with fertility
Bibliographic record
Abstract
Objectives were to quantify lying behavior (LB) during an estradiol and progesterone-based synchronization protocol, to assess risk factors for ovulation, pregnancy per AI (P/AI), and degree of behavioral change at estrus, and to investigate the associations between estrus LB and walking activity. Holstein cows (43.6 ± 11.0 kg of milk/d) were fitted with leg-mounted accelerometers. Total lying time/d (L_time), bout frequency (bout_N), average lying bout duration, and relative increase in walking activity (ACT%) were evaluated for 1,411 timed artificial insemination events. The day with lowest L_time or bout_N among d -2, -1, and 0 (day of timed artificial insemination) determined the day of behavioral estrus. The variables L_time% and bout_N% represent relative ratios between lowest L_time and baseline (d -7), L_time, and lowest bout_N, and baseline (d -7) bout_N, respectively [e.g., (lowest L_time/baseline L_time) × 100]. Correlation coefficients between L_time% and bout_N% and ACT% were -0.38 and -0.31, respectively. Estrus LB change was considered large if <75% of baseline and small if ≥75% of baseline for both L_time% and bout_N%; average lying bout duration did not change with estrus. Lowest L_time% and bout_N% corresponded to, respectively, 65 ± 21% (mean ± standard deviation; 447 ± 157 min/d) and 65 ± 24% (8.5 ± 4.0 bouts/d) of baseline. The change in L_time% at estrus was smaller when cows had milk yield above average; the change in bout_N% was smaller among multiparous cows and for estrus occurring in the colder season. Likelihood of ovulation was greater when there was larger change in L_time% [odds ratio = 4.9; ovulation rate = 93 (large change) and 76% (small change)], as well as when a corpus luteum was present at start of protocol (odds ratio = 3.6; in the model with L_time%). Likelihood of pregnancy at d 32 was 1.6 times greater for estrus with large change in LB [L_time% or bout_N%; P/AI = 34% (large change in L_time%) and 26% (small change in L_time%)]. Among estrus events with ACT% ≥300% (high intensity), classification by small or large L_time% did not influence P/AI at 32 d. The magnitude of LB change at estrus and its association with fertility suggest potential application toward improved use of activity monitors (e.g., increased estrus detection, fertility prediction). The contribution of LB to accuracy of estrus detection when physical activity is known remains to be addressed. The relationship between intensity of estrus expression and fertility requires further investigations of its physiological rationale and on-farm applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".