ALTERNATIVE AGRICULTURAL INSURANCE MODEL FOR CANOLA PRODUCERS (Brassica napus) OF LOW INCOME
Bibliographic record
Abstract
Canola cultivation is recently introduced in Mexico.The National Institute of Forestry, Agricultural and Livestock Research (INIFAP) released the Testigo Hyola-401 variety with average yields of 2.5-3.0 tons/ha, lower than those produced by Canada.This crop is planted in the State of Mexico, Jalisco and Tamaulipas, and is an economic alternative for small producers, therefore, production and market must be ensured through agricultural insurance that offers protection against climatic risks and possible contingencies of the market.The present work proposed the calculation of a risk premium through the ordinary least squares methodology in canola cultivation, using the variables yield (REND) and Average Rural Price (PMR) in each producing area in the period 2000-2019.It is reported that the cost of the national premium projected for 2021 would be $3,503/ha with a yield of 1.5 ton/ha., for the State of Tamaulipas $2,070.82/hawith a yield of 0.8 t/ha; for the state of Hidalgo of $1,941.57/hawith a yield of 1.5 t/ha; for the State of Mexico of $1,499.63/hawith a yield of 2.3 t/ha; and, for the state of Jalisco, $1,486.90/ha with a yield of 1.6 t/ha.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".