Effect of the Substitution of Sugarcane for Food Supply Crops in Goiás
Bibliographic record
Abstract
This article analyses the effect of replacing food crops with sugarcane in Goiás, according to mesoregions, between 2013 and 2020. The research intends to contribute to the discussion about the themes related to the changes that have occurred in the areas under plantation, production, and the value of sugarcane, rice, beans, corn, and soybeans. The database used is taken from IBGE's Municipal Livestock Production Survey. The results indicate that there was a rapid expansion of sugarcane production, which followed a similar direction as corn and soybeans, but with beans maintaining a very slow production rate. Sugarcane production is heavily concentrated in a single mesoregion of Goiás, which highlights a series of alerts regarding the spatial heterogeneity of this crop's production. The work concludes that there are strong indications that sugarcane is substituting rice production, but the same has not happened with beans.
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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 | 0.000 | 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) | 0.000 | 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".