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Record W7005115281

Perfil psicosocial de un grupo de pacientes sobrevivientes de cáncer de mama

2020· article· es· W7005115281 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyAffect (linguistics)Depression (economics)Habit
DOInot available

Abstract

fetched live from OpenAlex

El propósito de este estudio fue evaluar las características psicosociales de un grupo de pa-cientes sobrevivientes de CaMa. Mediante un muestreo no probabilístico, por conveniencia, participaron diecisiete mujeres pertenecientes al Grupo de Sobrevivientes de Cáncer de Mama “Ave Fénix”, del CMN “20 de Noviembre”, ISSSTE. Se realizó una investigación no experi-mental, con diseño transversal exploratorio. Las pacientes respondieron el Cuestionario de Regulación Emocional, la Escala de Ansiedad y Depresión Hospitalaria y la Escala de Toronto de Alexitimia, durante una de las sesiones mensuales que sostiene el grupo. Los resultados sugieren que el grupo presenta un nivel alto de alexitimia, un nivel leve de ansiedad y poca de-presión; además, utilizan la reevaluación cognitiva como estrategia regulación emocional. Estas características dan lugar a intervenciones psicosociales de grupo en su hospital

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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.136
GPT teacher head0.501
Teacher spread0.365 · 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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