MétaCan
Menu
Back to cohort

Análisis de las Buenas Prácticas de Manufactura (BPM) de los restaurantes del Mercado de Comidas Típicas, del cantón Archidona, provincia de Napo.

2020· article· es· W3032978450 on OpenAlexvenueno aff
Luis Eduardo Álvarez Cortez, Víctor Hugo del Corral Villaroel Del Corral Villaroel, David Agapito Zambrano Vera, Tania Cristina Cevallos Punguil

Bibliographic record

VenueConcienciaDigital · 2020
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Esta investigación analiza el cumplimiento de la Norma de Buenas Prácticas de Manufactura (BPM) en los restaurantes de comida típica del Mercado turístico municipal del cantón Archidona, provincia de Napo, siendo de tipo aplicada-descriptiva, utilizando el método cuantitativo y cualitativo, tomando como referencia la Norma Técnica Sustitutiva de Buenas Prácticas de Manufactura (BPM) para Alimentos Procesados (Art.1- 41), que consta en el Registro Oficial N. 555 del año 2015, también se empleó la técnica de la Observación y como instrumento de recolección de datos en relación a las BPM se utilizó Fichas de Observación elaboradas en base a la Norma de BPM, considerando 4 factores, que a través del Check list se comprobó el cumplimiento o no de esta norma. Los resultados determinan que, en los 14 establecimientos de comida típica, existe un bajo cumplimiento, en la aplicación de las Buenas Prácticas de Manufactura (BPM), sobre todo en relación a los procesos operativos de preparación, manipulación y comercialización de alimentos, esto afecta directamente a la calidad de los servicios entregados a los turistas y público en general que visitan el mercado de comidas típicas del cantón Archidona.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.238
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueConcienciaDigitalSame topicBusiness, Innovation, and EconomyFrench-language works237,207