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Record W4401108437 · doi:10.56469/hll.v10i11.1227

APLICACIÓN DE LAS 3R’S EN RESIDUOS SÓLIDOS: ESTUDIANTES FACULTAD DE CIENCIAS ECONÓMICAS Y EMPRESARIALES

2024· article· es· W4401108437 on OpenAlexaff
Anahí Beatriz Marca Vilacama, Marcos Julio Gironda Alarcón, Roberto Rivera Salazar

Bibliographic record

VenueHallazgos. · 2024
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La basura que se genera por parte de la población de los diferentes residuos son recolectados por el carro basurero de la Entidad Municipal de Aseo Sucre, los cuales son llevados al Botadero de Lechuguillas, estos residuos no son manejados o clasificadas de la mejor manera, generando un impacto medio ambiental negativo, ocasionando enfermedades y deterioro de los suelos. Se pretende medir la aplicación de las 3r’s (reutilización, reducción y reciclaje) de los residuos sólidos en los estudiantes de la Facultad de Ciencias Económicas y Empresariales, las cuales minimizarían en cierta medida el impacto medio ambiental que es causado por los residuos sólidos al darle un uso diferente y prolongando la vida útil de estos o reduciendo el consumo innecesario de ciertos productos que solo generan acumulación en depósitos finales. Para lograr el fin del presente trabajo se utilizó la técnica de las encuestas mediante el cuestionario diseñado con este propósito. En base a la metodología descriptiva y exploratoria, se pudo evidenciar el grado de aplicación de las 3R que son mínimas con relación al conocimiento de las consecuencias que conlleva el manejo inadecuado de los residuos.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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