Survey of reproduction management on Canadian dairy farms
Bibliographic record
Abstract
The objectives of this study were to (1) quantify current reproduction management practices, and (2) assess the association between these practices and herd reproductive performance on dairy farms in Canada. A bilingual survey was developed, validated, and administered from March to May 2014 to collect general and reproduction management and performance measures [annual 21-d pregnancy rate (PR), 21-d insemination rate (IR), and conception risk (CR)]. Associations between management practices and reproductive performance measures were tested using linear regression models. A total of 832 questionnaires were completed online and by mail, representing a response rate of 9%. On average, farms had 77 lactating cows (median=50) and 13 dry cows (median=10), and Holstein was the most common breed (92% of herds). Lactating cow housing was tiestall on 61% of the farms, freestall on 37%, and bedded pack on 2%. The average voluntary waiting period was 58 d in milk (DIM). The main reproduction management practice per farm was defined as the means employed for >50% of inseminations. Farms reported their main reproduction management practice for first and subsequent inseminations, respectively, as visual estrus detection (51 and 44% of herds), timed AI (21 and 23% of herds), automated activity monitoring (AAM; 10 and 10% of herds), other management practice (bulls; 2 and 2% of herds), and a combination of management practices (16 and 21% of herds). On farms using visual estrus detection, cows were observed for signs of estrus on average 3.5 times per day, for an average total of 36 min/d. The most common use of reproductive hormones was to synchronize ovulation using Ovsynch (58% of the farms). Average PR, IR, and CR were 17.6, 44.1, and 40.5%, respectively. In linear regression analyses adjusted for confounders, pregnancy rate was significantly associated with geographic region, housing (tiestall: PR=15.4%, freestall: PR=17.6%), herd size (<50 lactating cows: PR=16.2%, 50-100 cows: PR=16.5%, >100 cows: PR=17.8%), voluntary waiting period (≤60 DIM: PR=17.6%, >60 DIM: PR=15.9%), and frequency of insemination per day (once daily: PR=16.6%, twice or more daily: PR=18.1%). The main reproduction management practice at first and subsequent inseminations was divergently associated with IR and CR, but not with PR (visual heat detection: PR=17.4%, timed AI: PR=18.4%, AAM: PR=17.1%, combined practices: PR=18.2%).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".