Using unmanned aerial vehicles to record behavioral and physiological indicators of heat stress in cattle on feedlot and pasture
Bibliographic record
Abstract
Physiological and behavioral indicators of heat stress in cattle are time- and labor-intensive to measure, and difficult to observe in extensive feedlot and pasture settings. We proposed to record respiration rate and standing behavior using unmanned aerial vehicles. Videos were recorded above steers on feedlot in the morning (0830–1130) and afternoon (1400–1700) over 10 d between 25 July and 10 August and cows on pasture over 9 d between 19 and 29 August In the feedlot, video recordings on 925 individuals (264 black coated, 413 red, and 248 white) were obtained, varying in breed which included Black Angus, Hereford, Charolais, Canadian Speckle Park, and Simmental. On pasture, video recordings on 267 individuals (116 Black Angus and 151 Hereford) were obtained. Observer software was used to analyze videos. Respiration rate in feedlot cattle was the highest in black cattle, followed by red cattle, then white cattle. Coat color did not affect respiration rate in cows on pasture; temperatures on pasture were lower than in feedlots and the effect of coat color may not manifest until a certain heat load threshold. The probability that cattle would be standing increased with heat load index in feedlot and pasture settings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".