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Record W7132892276

Incidencia de la inflación en la toma de decisiones de inversión en las PYMES durante el periodo 2020-2023

2025· other· es· W7132892276 on OpenAlex
Karen Lisbeth Largo Noscué, Karen Natalia Navarro Ordoñez

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRepositorio Institucional UNIMAYOR · 2025
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Work (physics)Medium term
DOInot available

Abstract

fetched live from OpenAlex

Este estudio examinó cómo la inflación afecta las decisiones de inversión de las PYMES en Colombia entre 2020 y 2023, un tiempo caracterizado por gran inestabilidad económica y constantes aumentos de precios. Se observó que, debido al aumento en los costos operativos, muchas PYMES pusieron en primer lugar estrategias para sobrevivir en lugar de enfocarse en crecer. El acceso limitado al crédito, debido a la subida de las tasas de interés, redujo aún más su capacidad para invertir en tecnología, infraestructura o personal. También, las decisiones de inversión cambiaron según el sector económico, siendo más cuidadosas en campos como el comercio minorista y los servicios personales.

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.

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)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0040.003
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 head0.005
GPT teacher head0.277
Teacher spread0.272 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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