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Análisis de las falencias del sector apicultor en la provincia del Guayas

2020· article· es· W3116521671 on OpenAlexaff
Willian V. Rosillo, Isabel Moreno Vivanco, Edgar Fernando Vasquez Reyes, Diana Guadalupe Soancatl Rodríguez

Bibliographic record

VenueESPACIOS · 2020
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsASTER
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

El sector de la miel de abeja en otros países es muy dinámico y desarrollado, pero en el Ecuador es otra la realidad, en especial en la provincia del Guayas que, aunque es una provincia apta para la apicultura no está siendo explotada de manera correcta causando así un desabastecimiento en el mercado el cual es cubierto con importaciones provenientes de China, México, Perú y Argentina, otro principal problema es el número total de mieles adulteradas que en algunos casos son difíciles de identificar por el consumidor. En el presente trabajo se hace un análisis del sector (producción. comercialización, marcas, precios, producto de origen) para así dar una mayor compresión al lector de la realidad por la cual atraviesa el sector apicultor.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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