Factors affecting dairy calf price in auction markets in Québec, Canada: 2008–2019
Bibliographic record
Abstract
Dairy calves not kept for replacement are sold at young age in Québec auction markets for white and grain-fed veal calf production. The province of Québec produces 80% of the Canadian veal meat, but little information is available on the factors associated with the calves' price per crude weight (Can$/kg; Can$1 = US$0.78 at time of writing). The characteristics of calves sold in Québec auction markets from 12 complete years (2008-2019) were retrospectively studied. The calves' weight, breed and sex, the year and season of sale, the auction site, as well as the estimated distance traveled between the farm of origin and the auction site were analyzed as potential covariates associated with calf price. Two multivariable logistic models associated with low sale value (below the 10th or the 25th percentile of the day price) and 2 models associated with good sale characteristics (above the 50th or the 75th percentile of the day price) were built. The median distance between the farm and the auction site was 52 km (interquartile range: 30-95 km). Only 5% of calves traveled distances greater than 220 km. The weight, breed, sex, and auction sites explained most of the variability in the different models. Distance traveled and multiple interactions were also significantly associated with the outcomes. Calves with body weight from 48 to <56 kg were sold in higher percentiles of the day than lighter or heavier calves. Beef-crossed calves had better sale prices than Holstein, whereas colored dairy calves had lower sale characteristics than both Holstein and beef-crossed calves. The effect of distance traveled was complex, varying depending on the model and interactions, and explained a small portion of the total deviance in every model. Calves traveling from distances ≥110 km had lower sale characteristics in summer and fall in the different studied models. This study gives relevant insights on calves' characteristics associated with good versus low sale prices in Québec auction markets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".