Bibliographic record
Abstract
Disposition or temperament of cattle is a measure of the animal's relative docility, wildness, and handling ability during processing in the pen as well as in the handling facilities. Easily excitable animals compromise both their own safety and the safety of handlers. The Iowa Tri-County Steer Carcass Futurity collects sires, dams, and birth dates from cow-calf producers who retain ownership, as well as growth data, health treatments, disposition scores, and complete carcass data on steers and heifers. In the last 10 years data has been collected on 66,620 head of cattle from 23 states and Manitoba. Cattle are disposition scored at on-test, reimplant, and first sort; the cattle in the second harvest group are scored one additional time. Based on their average disposition score, the cattle were grouped as docile, restless, and aggressive. When compared to docile cattle, aggressive cattle gained less in the feedlot (2.91 vs 3.17 lb/day; 1.32 vs 1.44 kg/day), produced fewer Choice carcasses (58.1 vs 72.4%), more Select carcasses (36.2 vs 23.3%), and the black-hided cattle produced a lower percentage of Certified Angus Beef (CAB) carcasses (14.3 vs 29.1 %). Morbidity rates were similar across disposition scores; however, death loss increased significantly as disposition scores increased. Non-replacement heifers had higher disposition scores than steer mates, as cow-calf producers selected for more docile replacement heifers. Average profit for docile cattle was $46.63 per head compared to $7.62 per head for aggressive cattle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.359 | 0.189 |
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".