MétaCan
Menu
Back to cohort
Record W7073949487

Un programme d'art-thérapie innovateur destiné aux patients atteints de cancer

2015· article· fr· W7073949487 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languagefr
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsFace (sociological concept)MEDLINEPalliative careCancer treatment
DOInot available

Abstract

fetched live from OpenAlex

L'art-thérapie est une démarche de guérison qui intègre les soins physiques et le soutien affectif et spirituel et qui permet aux patients de faire appel à la créativité pour faire face à leur vécu du cancer. Un nouveau programme d'art-thérapie a été conçu pour fournir à des patients atteints de cancer diverses possibilités d'explorer la Collection McMichael d'art canadien et d'examiner leurs propres émotions face à leur vécu du cancer et ce, en combinant des activités dans la galerie proprement dite et dans un studio. Le rôle de l'animatrice consistait à faciliter l'interprétation des dessins des participants en vue d'en révéler la signification. Cet article présente les perspectives des patients relatives à ce nouveau programme d'art-thérapie. L'analyse de contenu de la rétroaction des participants a fourni des renseignements sur la structure, le processus et les résultats du programme. L'évaluation de ce programme d'art-thérapie et d'éducation muséale indique qu'il offre de nombreux avantages aux patients atteints de cancer, notamment en matière de soutien, de force psychologique et de compréhension intime du vécu du cancer.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.002

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 head0.215
GPT teacher head0.515
Teacher spread0.300 · 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 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicTheoretical and Computational PhysicsFrench-language works237,207