443 広島県の観光景観画像に対する心理的評価に関する研究 : その4-評価間の関連性-
Bibliographic record
Abstract
Vocalization of cattle in commercial slaughter plants is associated with observable aversive events such as prodding with electric prods, slipping in the stunning box, missed stuns, sharp edges on equipment or excessive pressure form a restraint device. A total of 5806 cattle were observed during handling and stunning in 48 commercial slaughter plants in the United States, Canada and Australia during the calendar year of 1999. Each animal was scored as either a vocalizer or a non-vocalizer. In 20 plants (42%), 0-1% of the cattle vocalized, in 12 plants (25%) 2-3% vocalized, in 12 plants (25%) 4-10% vocalized and in four plants (8%) more than 10% vocalized. In three plants repeated use of an electric prod on 95% or more of the cattle that balked and refused to move was associated with vocalization percentages of 17, 16 and 12%. In five plants, the percentage of cattle that vocalized was reduced by making modifications to plant equipment. Reducing the voltage on a rheostat controlled electric prod reduced the vocalization percentage from 7 to 2% in the first plant. In three other plants, the incidence of cattle backing up and balking was reduced by illuminating a dark entrance or adding a false floor to a conveyor restrainer. A false floor eliminates the visual cliff effect. The percentage of cattle that vocalized was reduced from 8 to 0%, 9 to 0% and 17 to 2%. Since balking was reduced, electric prod use was also reduced. In the fifth plant, reduction of the pressure exerted by a neck restraint reduced the percentage of cattle that vocalized from 23 to 0%. In the five plants where modifications were made, a total of 379 cattle were observed prior to equipment modifications and 342 after modification. The mean percentage of cattle that vocalized was 12.8% before the modifications and 0.8% after the modifications (P<0.001). Vocalization scoring can be used to identify handling and equipment problems that may compromise animal welfare.
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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 | 0.000 | 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 | 0.000 | 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) | 0.003 | 0.005 |
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; both teacher heads agree on what is shown here.
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".