Survey of coat and reproductive age of quarter horses used in vaquejada in northeast micro-regions of Brazil
Bibliographic record
Abstract
Aimed to evaluate the coat and Quarter reproductive age used in equine production used in Vaquejada in micro regions of the Northeast. They used information from 264 horses, taken from the database of the Association of Quarter Horse Breeders (ABQM). Were collected individual information: date of birth, sex and animal fur, number of copies of disputed official Vaquejada, better and worse placed, cumulative score in ABQM, coats and dates of parents' birth (31), coats and birth dates mothers (257). There was a higher frequency (P 0.05). There was no correlation (P>0.05) between the number of children and the stallion entry age at reproduction. There was a greater preference for coats alaza (20.08%) and bay Tumbleweed (21.97%) in the progeny; the stallions were 34.47% and 29.92% Tumbleweed bay brown; while the matrices were 41.29% and 23.48% alazas brown. Stallions bay Tumbleweed survived longer playback and more offspring. However, it was observed that while 93 of the 264 animals are children of parents at least one bay to bay coat or Tumbleweed, only 52 animals showed that the coat. It is concluded that the coat of stallions is related to greater frequency of use in reproduction; however, to obtain a coat expected in the progeny, we need to carry out a genetic study and not only phenotypic.
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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 | 0.001 |
| 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".