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Record W3125340859

Difusão biotecnológica: a adoção dos transgênicos na agricultura

2014· article· pt· W3125340859 on OpenAlexaboutno aff
Vieira Filho, José Eustáquio Ribeiro

Bibliographic record

Venuewww.ipea.gov.br · 2014
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsLogistic functionLegalizationAgricultural scienceAgricultureProduction (economics)Function (biology)Agricultural economicsBiotechnologyEconomicsBiologyStatisticsMathematicsPolitical scienceMicroeconomicsLawGeneticsEcology
DOInot available

Abstract

fetched live from OpenAlex

The genetic engineering techniques are essential in modern agriculture and, at the same time, demand regulation on several levels. The diffusion of planting genetically modified organisms (GMOs) has grown since 1996, notably in the United States, Argentina and Canada. In Brazil, the production of genetically modified soybeans began illegally and with a slow adoption rate in 1997. The legalization of genetically modified soybean planting in 2003 intensified the spread of biotechnology in Brazil. This study presents two epidemic models of technology diffusion: exponential (central source) and logistic (contagion). The results obtained suggest that the diffusion process is best described by a logistic function. Although the study does not discuss in detail the function's parameters, it is understood that the trajectory of the logistic curve is fairly complex, since there is no equilibrium for fixed values over time.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.244
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venuewww.ipea.gov.brSame topicGenetically Modified Organisms ResearchFrench-language works237,207