Predicción, del peso vivo en ganado bovino, a partir de mediciones corporales.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study took place in a cattle ranch working with double-purpose cattle, in the Department of Jutiapa, Guatemala, with the objective of calibrating a model of cattle measuring tape, with body measures, during the months of April, May and July, 1993. The measures were taken from 456 cattle heads, and the measuring variables comprehended: the torax diameter (TD), the body lenghth (BL), the live weight in kilograms (LW), and the age in years (AG). Cattle food was mainly pastures of “African Star” and “Jaragua” varieties, and other natural species. The herd produces milk all year round with a daily milking, and calves suckle until eight months old. The cattle measurements information was analyzed throughout fixed-effect models, including the TD, BL and AG variables, to determine the contribution of each effect for the live weight predictions. Two lineal multiple regressive models were adjusted by natural logarithm and by base-10 for males and females respectively. The analysis determined that in the studied population, the TD, BL and AG variables can be used to predict the live weight, according to the animal’s sex.
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.
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) | 0.001 | 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 it