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Record W4414497334 · doi:10.53897/li.2025.0026.ucol

Mundiales de Futbol Varonil 2022 y Femenil 2023

2025· book· es· W4414497334 on OpenAlexaff
Eloy Altuve Mejía, Rita Lorena Arambuena, Heloísa Helena Baldy dos Reis, Felipe Andrés Bernal Sandoval, Héctor Adolfo Bernal Sandoval, María Claudia Benassini Félix, María del Rosario Bringas Benavides, Oswaldo Ceballos Gurrola, Alejandra Chávez Ramírez, Javier Arturo Hall López, Gloria Janett Hernández Blancas, David Ibarrola, Miguel Ángel Moreno Hidalgo, Roberto López Urbano, Samantha Medina Villanueva, Francisco Javier Mendoza-Farias, Rocío Abril Morales Loya, Jorge Rosendo Negroe Álvarez, Paulina Yesica Ochoa Martínez, Felipe Tavares Paes Lopes, Alan Emmanuel Pérez Barajas, Angélica Yedit Prado Rebolledo, Luis Alberto Rivera, Omar Rivera, Luis Tomás Rodénas Cuenca, Miguel Muñoz Bautista, Ciria Margarita Salazar, J. Arenas, Cristina Cañadas Monroy, Beatriz Elena. Compiladora López Vélez, Daniel Zambaglione, Mariana Zuaneti Martins

Bibliographic record

VenueUniversidad de Colima eBooks · 2025
Typebook
Languagees
FieldSocial Sciences
TopicSports and Physical Education Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBasketballFootballPromotion (chess)Race (biology)

Abstract

fetched live from OpenAlex

El libro “Mundiales de futbol varonil 2022 y femenil 2023: Transversalidades y conocimientos multidisciplinares” presenta una visión profunda y crítica sobre el impacto social, cultural, económico y educativo de los dos eventos futbolísticos más importantes de la industria del entretenimiento con atención mundial. Las plumas que han coincidido en esta compilación de diversas latitudes de América Latina y México destacan la relevancia de analizar estos torneos más allá del simple espectáculo deportivo, invitando a reflexionar sobre el futbol como un fenómeno que teje identidades, moviliza pasiones y refleja las estructuras y luchas sociales contemporáneas.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.310
Teacher spread0.294 · 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 teacher head, not a consensus.

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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