Dairy cows continuously-housed in tie-stalls failed to manifest activity changes during estrus
Bibliographic record
Abstract
Felton, C. A., Colazo, M. G., Ponce-Barajas, P., Bench, C. J. and Ambrose, D. J. 2012. Dairy cows continuously-housed in tie-stalls failed to manifest activity changes during estrus. Can. J. Anim. Sci. 92: 189-196. While pedometers are effective for estrus detection in free-stall herds, their efficacy in tie-stalls is not established. The objectives were to determine if pedometers equipped with a behavior tag for monitoring lying activity (AfiMilk Pedometer Plus Tag system) can accurately record cow activity, and if they can facilitate estrus detection in dairy cows continuously housed in tie-stalls. Nineteen lactating Holstein cows were subjected to estrus induction with prostaglandin F2a, and 18 pregnant cows served as controls. Activity was monitored for 10 d using pedometers and 24-h video recording. Pedometer and video records were compared for 6 d surrounding estrus; stepping (rc=0.85; P<0.01), lying time (rc=0.94; P<0.01), and lying bouts (rc=0.89; P<0.01) were highly correlated. Progesterone concentrations confirmed that 17 of the 19 cows responded to estrus induction; 16 of those 17 cows ovulated. Changes in mean daily activity did not differ (P>0.05) between estrus-induced cows and controls, or in the estrus-induced cows in the 48 to 72 h preceding the day of ovulation. In conclusion, while the pedometers accurately recorded cow activity in lactating cows housed in tie-stalls, they could not facilitate estrus detection because cow activity did not significantly change during estrus.
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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 | 0.000 | 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".