Bibliographic record
Abstract
Cualquiera que trabaje en la industria lactea sera consciente de que hay una gran variacion en el diseno de los corrales de parto. Parte de esta variabilidad es debida a la falta de investigacion sobre que tipos de ambiente son los mejores para la vaca durante el parto. Una investigacion de la Universidad de British Columbia (Canada) sobre el diseno de los corrales de parto mas apropiados ha permitido conocer las preferencias de las vacas a este respecto a traves de una serie de experimentos. A continuacion se describen los resultados de tres de estos experimentos disenados para determinar que caracteristicas son importantes en el diseno de los corrales de parto. Trabajos anteriores realizados con ganado bovino salvaje o con animales en sistemas extensivos han estudiado la eleccion de las vacas en el momento del parto en el ambiente natural. En este ambiente, normalmente las vacas abandonan el ganado para encontrar una zona apartada para parir; por ejemplo, una zona con hierba alta o de arbustos con tierra blanda. De estas observaciones se puede extrapolar que las vacas en explotaciones intensivas buscaran separarse de sus companeras de rebano (y de otras amenazadas percibidas) y usaran un lugar escondido para parir si se les da la oportunidad.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".