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Record W4414958484 · doi:10.59514/2539-0686.3664

Capacidad de Carga, Sendero Ecoturístico, Hotel Magüipi

2024· article· es· W4414958484 on OpenAlexaboutno aff
Paula Stefanny Rueda Castañeda, Daniel Fabian Villanueva Parra, Juan Pablo Mariño Jiménez

Bibliographic record

VenueRevista Gestión y Finanzas · 2024
Typearticle
Languagees
FieldSocial Sciences
TopicUrbanism, Landscape, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Work (physics)Quarter (Canadian coin)Tourism

Abstract

fetched live from OpenAlex

El senderismo es una actividad que requiere de planificación y manejo para mitigar el potencial impacto ambiental resultante, puesuna mala práctica puede traer consigo daños irreparables. Para ello, resulta indispensable la elaboración de estudios de capacidad de carga, como instrumentos que contribuyan a la gestión y conservación de los escenarios naturales con vocación turística, y que permitan a los visitantes disfrutar experiencias de alto nivel capaces de satisfacer sus expectativas. El objetivo del presente estudio es determinar la capacidad de carga turística del "Sendero Ecológico del hotel Magüipi, garantizando una explotación racional y sostenible. Este estudio se realizó aplicando una metodología cuantitativa a partir del modelo de Cifuentes, el cual busca establecer el número máximo de visitas que puede tolerar un área protegida con base en las condiciones físicas, biológicas y de manejo que se presentan en determinado momento. Se identificaron los factores de corrección por medio de una serie de cálculos dando como resultado 435 visitantes que pueden transitar a diario por el sendero sin ocasionar daños al ecosistema o degradación de los recursos.

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)0.006
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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