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Record W7054462428

Alexitimia en adolescentes de tercero de bachillerato pertenecientes a una institución de Cuenca

2020· dissertation· es· W7054462428 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional (Universidad de Cuenca) · 2020
Typedissertation
Languagees
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsPersonaContext (archaeology)Linea
DOInot available

Abstract

fetched live from OpenAlex

La etapa de la adolescencia es un área de interés a ser estudiada debido a los diversos cambios a nivel físico, social y sobre todo emocional que pueden afectar el óptimo desarrollo de esta población. Respecto al nivel emocional se identifica como Alexitimia (AL) a la incapacidad de una persona para describir y expresar verbalmente sentimientos propios, así como identificar estados afectivos de los demás. Es así que, el propósito de la presente investigación de carácter descriptivo se centra en identificar el porcentaje de adolescentes de tercero de bachillerato de la Unidad Educativa Técnico Salesiano que presentan AL. Para efecto de ello, a una muestra conformada por 175 participantes entre 16 y 18 años de edad correspondientes al sexo masculino y femenino, se les aplicó la Escala de Toronto de Alexitimia (Martínez-Sánchez, 1996), adaptación española. Los resultados obtenidos permitieron conocer el índice de AL según el sexo y el factor de la AL establecido en el instrumento, que mayor influencia tiene en los adolescentes. En conclusión, un porcentaje considerable de participantes presentan AL marcada (33.1 %) y posible AL (31.4 %), lo cual debe tomarse en cuenta puesto que es un factor de riesgo para ciertos trastornos y problemas a los que es más vulnerable la población adolescente.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.266
Teacher spread0.256 · 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
Published2020
Admission routes1
Has abstractyes

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