Studying the relationship between on-farm environmental conditions and local meteorological station data during the summer
Bibliographic record
Abstract
High ambient heat and humidity have profound effects on the production, health, profitability, and welfare of dairy cattle. To describe the relationship between summer temperature and relative humidity in the barn and determine the appropriateness of using meteorological station data as a surrogate for on-farm environmental monitoring, a study was conducted on 48 farms in Ontario, Canada, over the summer (May through September) of 2013. Within-barn environmental conditions were recorded using remote data loggers. These values were compared with those of the closest official meteorological station. In addition, farm-level characteristics and heat-abatement strategies were recorded for each farm. Environmental readings within the barn were significantly higher than those of the closest meteorological station; however, this relationship varied greatly by herd. Daily temperature-humidity index (THI) values within the barn tended to be 1 unit higher than those of the closest meteorological station. Numerically, 1.5 times more mean daily THI readings were in excess of 68 (heat stress threshold for lactating dairy cows) in the barn, relative to the closest meteorological station. In addition, tiestalls, herds that were allowed access to pasture, and herds that had no permanent cooling strategy for their cows had the highest mean and maximum daily THI values. Minimum daily THI values were almost 4 units higher for tiestall relative to freestall herds. Overall, due to farm-specific and unpredictable variability in magnitude of environmental differences between on-farm and meteorological station readings, researchers attempting to study the effects of environment on dairy cows should not use readings from meteorological stations because these will often underestimate the level of heat stress to which cows are exposed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".