Testing the ability of contact mats to identify problematic stall configurations
Bibliographic record
Abstract
Comparing the frequency of cow contact with stall rails across multiple stall designs may help to determine which stall configurations best promote cow ease of movement and reduce injury risk. The objective of this study was to compare the frequency of cow contact with the dividers across different stall treatments using the contact mat (CM) system to identify problematic stall designs. A total of six stall treatments were each tested against for six consecutive weeks against control (CON) stall condition: three treatments that modified the placement of the tie-rail (TRFARM, TRNEW1, TRNEW2) and three separate treatments that increased chain length (LCL), doubled stall width (DSW), and shortened manger wall (SMW) height. CM were affixed to the stall dividers to record the frequency of cow contact per second. Cows were ranked in descending order from highest frequency of divider contact to lowest frequency of divider contact for each week. TRNEW1 and TRNEW2 were the only stall treatments with a consistently lower frequency of divider contact than CON, whereas DSW was consistently higher than CON. The results suggest that the CM system can be used to identify problematic stall configurations to independently substantiate findings related to cow comfort.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 |
| 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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".