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Record W4390428145 · doi:10.22533/at.ed.216412402014

ALTERNATIVE AGRICULTURAL INSURANCE MODEL FOR CANOLA PRODUCERS (Brassica napus) OF LOW INCOME

2023· article· en· W4390428145 on OpenAlex
Adriana Miranda-Medina, Rogel Fernando Retes Mantilla, Luis Alfonso Bonilla-Cruz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientific Journal of Applied Social and Clinical Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaBrassicaAgricultureBusinessCrop insuranceAgricultural economicsAgricultural scienceAgronomyEconomicsEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.318
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it