Análise do custo de transporte de fertilizantes com uso de modelagem digital de terreno.
Bibliographic record
Abstract
The Brazilian fertilizer industry is subject to a tax system that can cancel the competition of the national product with regard to imported, depending on the geographic configuration of the domestic supply and the fact that the imported products take advantage of tariff benefits.Such benefits are justified by the large dependence of the Brazilian agriculture has this important input.Therefore, the location of the consumer market in relation to the main ports of entry of the input and the domestic industry is a strategic information to the market and the viability of domestic investment projects.This study analyzed the logistics costs imposed on the main imported fertilizers by using a new methodology: the use of a digital terrain model.The model was generated interpolating price indicators constructed from the variables that act in the formation of prices of imported fertilizers by three different methods.The product of the study is a digital model that describes the behavior of the imported fertilizer price in a continuous manner over the surface.This model was used to analyze the coverage area of the imported fertilizer for each of the main ports and prepare simulations from the manipulation of model variables. .
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".