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Record W37607030 · doi:10.1172/jci168192

El servicio de comedor en un sitio de aprendizaje real

2006· article· en· W37607030 on OpenAlexfundno aff
Anna Freixas Farré

Bibliographic record

VenueRES : Revista de Educación Social · 2006
Typearticle
Languageen
FieldHealth Professions
TopicNursing care and research
Canadian institutionsnot available
FundersNHLBI Division of Intramural ResearchNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchAmerican Heart Association
KeywordsHumanitiesArtCartographyGeography

Abstract

fetched live from OpenAlex

Con este articulo pretendo, en primer lugar, daros cuatro pinceladas generales de las consecuencias del traumatismo craneoencefálico y del daño cerebral sobrevenido, para que los lectores desconocedores de este ámbito puedan hacerse una mínima idea de las afectaciones con las que los afectados viven a raíz de este daño. En segundo lugar conoceremos brevemente a TRACE, la Asociación Catalana de Traumáticos Craneoencefálicos y Daño Cerebral, sus orígenes, sus objetivos y las áreas de trabajo. Para finalizar, abordaremos el Espacio TRACE, el programa de integración social específico para los afectados: qué entendemos por Espacio TRACE, su objetivo, el perfil de los usuarios y las actividades que lo componen. Una de estas actividades es la protagonista del artículo: el servicio de comedor que la asociación tiene en un restaurante del barrio y, al fin y al cabo, la integración social que se persigue cada día con esta labor de intervención socioeducativa enmarcada en un ambiente totalmente normalizado (un restaurante) y con un rol social también normalizado (comensales).

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.018

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 head0.028
GPT teacher head0.451
Teacher spread0.423 · 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".

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Citations0
Published2006
Admission routes1
Has abstractyes

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Same venueRES : Revista de Educación SocialSame topicNursing care and researchFrench-language works237,207