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Record W3161412819 · doi:10.52080/rvgv26n94.24

Aproximación conceptual para la calidad en la etapa pre inversión

2021· article· es· W3161412819 on OpenAlexaff
Luis Alexis Aguilera García, Yosvani Orlando Lao León, Inocencio Raúl Sánchez Machado, Zulma María Ledesma Martínez

Bibliographic record

VenueRevista Venezolana de Gerencia · 2021
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsInversa Systems (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

El objetivo del artículo es analizar la calidad en la etapa de pre inversión de proyectos, dada la dispersión de criterios identificada al respecto. Se analizaron las diferentes perspectivas y tendencias de la calidad de la etapa de pre inversión, que constituye la etapa inicial de los proyectos, a través de la utilización de métodos teóricos como: análisis-síntesis, inductivo-deductivo y sistémico estructural bajo un enfoque bibliométrico. Se consultaron las publicaciones científicas en la Web of Science, Dimensions, Scielo y Redalyc, cuyo análisis permitió reconocer el creciente interés en la temática durante el año 2020 y el protagonismo de la revista científica Venezolana de Gerencia en su divulgación. Como principal resultado, se propone una aproximación conceptual de la calidad de la etapa de pre inversión que contiene las variables: cumplimiento de características de calidad, responsabilidad social, satisfacción de las partes interesadas, costos, plazos y fiabilidad; resultantes del análisis de correlación de las palabras clave más utilizadas en las definiciones identificadas. Este resultado podrá constituir el basamento teórico para el diseño de indicadores y metodologías para la evaluación y mejora de la calidad en la etapa de pre inversión.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.247
Teacher spread0.217 · 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
Published2021
Admission routes1
Has abstractyes

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