EFICIÊNCIA TÉCNICA NA PRODUÇÃO DE LEITE EM PEQUENAS PROPRIEDADES DA MICRORREGIÃO DE VIÇOSA.
Bibliographic record
Abstract
Neste trabalho, avaliou-se a eficiência técnica em pequenas propriedadesprodutoras de leite da Microrregião de Viçosa, MG, assistidas no âmbito do convênioUFV/Nestlé (PDPL). Essas propriedades foram classificadas segundo o tamanho e ograu de sangue do rebanho, propondo medidas com vistas ao uso mais eficiente dosrecursos produtivos. Utilizou-se um modelo de Análise Envoltória de Dados (DEA)para identificar as propriedades eficientes e ineficientes. Verificou-se que a maioria daspropriedades, sob a pressuposição de retornos variáveis, foi eficiente, enquanto sob apressuposição para retornos constantes, ineficiente. Observou-se que as propriedades,no período de 1999-2003, tornaram-se mais semelhantes, ou seja, evoluíram para padrõesde maior eficiência técnica em seus processos produtivos.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".