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Record W4292693351 · doi:10.3407/rpn.v5i1.6711

Huerta para la Enseñanza

2022· article· es· W4292693351 on OpenAlexvenueno aff
Santiago Andrés Angarita Martínez, Juan Hernández-Lalinde, Claudia Marcela Martínez Suarez

Bibliographic record

VenueRevista Productos Naturales · 2022
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical scienceSociology

Abstract

fetched live from OpenAlex

Los usos de prácticas pedagógicas convencionales, y la necesidad de cumplir con los requerimientos de estar a la par: la práctica de competencias y la catedra de clase. Por esto se hace necesario abrir espacios donde se vaya de la mano lo visto en clase y la solución de problemas; sin embargo en la actualidad, vivimos en un tiempo de avances tecnológicos, que hace necesario articular todas las áreas del saber dentro de una sola que permita al estudiantes, encontrar un balance entre los que aprende y lo necesita; por tanto se determinó que, a partir de una huerta convencional, los estudiantes encuentren diferentes necesidades para solucionar problemas de la vida diaria; con un aprendizaje lógico y didáctico

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.008
Scholarly communication0.0100.009
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.006

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 head0.024
GPT teacher head0.296
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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