RELACIÓN ENTRE EL NIVEL DE TECNOLOGÍA Y LOS ÍNDICES DE PRODUCTIVIDAD EN FINCAS GANADERAS DE DOBLE PROPÓSITO LOCALIZADAS EN LA CUENCA DEL LAGO DE MARACAIBO Relationship Between Level of Technology and Productivity Índices of Dual-Purpose Cattle Farms Located on The Maracaibo Lake Basin
Bibliographic record
Abstract
In order to study the relationship between the levels of technology and productivity indicators of dual-purpose cattle farms located in the Jesus E. Lossada, La Canada de Urdaneta y Rosario de Perija Municipalities, 102 farms were selected by random sampling and K-mean algorithm to create the technological groups. Three technological groups (TGs) were identified: low (TG ), middle (TG ) and high (TG ). Later, the partial productivity means of different groups were compared by variance analysis and the Duncan test was utilized to evaluate the differences among the means. The TG showed high partial productivity in several indicators but only milk liters by total-cow and by labor productivity were statistically significant (P<0.05). Also, economical indicators such as income by total-cow, total income, profit and gross profit resulted statistically different from TG and TG . These results allow concluding that TG showed a higher herd and labor productivity and lower cost-income relationship due to differences in the farm management of TG with respect to other groups. There is a straightforward relationship among technological levels and economical indicators. Profit and gross profit increases as the farm move into higher technological level.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".