Effects of Heifer Calving Date on Longevity and Lifetime Productivity in Western Canada
Bibliographic record
Abstract
The objective of this study is to determine the effect of calving early as a heifer on lifetime production in western Canada. This study evaluated the longevity and life time production data on 211 individual heifers (data gathered for 16 years) at the Western Beef Development Centre (WBDC), Saskatchewan. Heifers were classified as calving in the first (period 1; n= 87), second (period 2; n = 66), or third (period 3; n = 58) 21-day period of the calving season. For each subsequent calf born to the cow, calving period was reassigned in the same manner. The current study showed that the average life time number of calves weaned for heifers that calved in the 1st, 2nd, and 3rd 21-day period was 5.4 ± 0.32, 4.5 ± 0.37, and 4.2 ± 0.39, respectively. Retaining percentage rate of period 1 cows was 4.3-17.8 and 2.1-19.1% units greater than those of period 2 and period 3 cows, respectively. Period 1 heifers had the greatest life time produced total cumulative weaning weight (p <0.01) value of 1157 kg/cow, followed by period 2 and period 3 heifers, 947 and 841 kg/cow, respectively. Period 1 cows generated an additional $718 to $1077 in weaned calf revenues over their lifetime. This study suggested that, in western Canada, heifers that calved earlier had greater pregnancy rates, remained in the herd longer, and produced one more calf in their lifetime than those that calved in the later periods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".