Análise dos preços do boi e da carne nos diferentes elos da cadeia produtiva
Bibliographic record
Abstract
The beef chain is cyclically influenced by several factors that affect the prices of meat in retail and, consequently, the prices paid to the rural producer. The objective of this study was to analyze cattle and meat prices in the different links of the production chain during the months of the year. The prices paid by ox and beef were collected every fortnight in four segments of the chain: young cattle producer, fat cattle producer, slaughterhouse and retailers. Analysis of variance (ANOVA), Tukey test and linear correlation of Pearson were performed. The first quarter of the yearshowed the highest prices for all links in the chain, while the third quarter showed the lowest price. Retail sources had similar annual average prices among themselves. The highest values of correlation occurred between the price of the young cattle ( .810) and the price of the beef ( .855) with the selling price of the meat by slaughterhouse. Lower correlations occurred between the price of meat sold by the retailer and the selling price of the meat through the slaughterhouse ( .425). The fat cattle price was the largest coordinator of the other prices in the beef chain ( .886), and is the biggest regulator of the young cattle price, price of meat sold to retail, but not the price of meat sold to the consumer.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".