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Record W4416805453 · doi:10.65330/am.v6i1.37

LOS JUEGOS TRADICIONALES EN LA FILATELIA: ESTUDIO PRAXIOLÓGICO Y MULTICULTURAL DE LA ACTIVIDAD LÚDICA

2022· article· W4416805453 on OpenAlexaboutno aff

Bibliographic record

VenueAcción Motriz · 2022
Typearticle
Language
FieldSocial Sciences
TopicSports and Physical Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Poison controlPeriod (music)

Abstract

fetched live from OpenAlex

La filatelia temática nos muestra de manera detallada la evolución de la humanidad. Precisamente, ha quedado reflejado en esta enciclopedia en miniatura: obras de arte, gobernantes, inventos, uniformes, vestidos, heráldica, flora, fauna, vegetación, etc. El fenómeno deportivo también ha estado presente en el correo postal, ya que se han inmortalizado Mundiales de Fútbol, Olimpiadas, Tour de Francia, deportistas destacados de alto nivel, etc. Con el fin de delimitar el estudio, hemos focalizado la investigación en los sellos emitidos en el año 2009 por la UPAEP (Unión Postal de las Américas, España y Portugal) basándonos en la praxiología motriz. La organización está formada, por los siguientes países: Antillas Holandesas, Argentina, Aruba, Bolivia, Brasil, Canadá, Colombia, Costa Rica, Cuba, Chile, Ecuador, El Salvador, España, Estados Unidos de Norteamérica, Guatemala, Haití, Honduras, Nicaragua, Panamá, Paraguay, Perú, Portugal, República Dominicana, Surinam, Uruguay y Venezuela. Las fuentes utilizadas para la búsqueda de datos han sido casi siempre primarias. En este sentido, se han revisado diferentes soportes de catálogos fotográficos, postales, revistas especializadas, libros sobre la práctica de juegos, etc, pero fundamentalmente catálogos filatélicos. Por último, mostramos los datos y resultados obtenidos y finalizamos con unas conclusiones y prospectiva de futuro para posteriores investigaciones.

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), 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.335
Teacher spread0.319 · 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
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
Published2022
Admission routes1
Has abstractyes

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