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Record W1913716031

Doença de Crohn e retocolite ulcerativa inespecífica: alexitimia e adaptação

2008· article· pt· W1913716031 on OpenAlexaboutno aff
Lilian Pereira de Medeiros Guimarães, Elisa Médici Pizão Yoshida

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Languagept
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScaleCorrelationMedicineCrohn's diseaseDiseaseInternal medicineGastroenterologyNegative correlationClinical psychology
DOInot available

Abstract

fetched live from OpenAlex

La enfermedad de Crohn y la Retocolitis Ulcerativa Inespecífica (RCUI) son enfermedades gastrointestinales inflamatorias. Como la misma puede afectar severamente la vida de sus portadores, el estudio objetivó investigar la eficacia adaptativa y el nivel de alexitimia, de estos pacientes. Se investigo también la medida en que cada una de estas medidas se correlacionaba con la severidad de los síntomas gastrointestinales y con el tiempo de la enfermedad. La muestra fue formada por 25 pacientes, ambulatoriales, con Enfermedad de Crohn (52%) y RCUI (48%). Instrumentos: Escala Diagnóstica Adaptativa Operacionalizada - Redefinida (EDAO-R) y Toronto Alexithymia Scale (TAS). Resultados: 1. alto comprometimiento en la calidad de adaptación y no nivel de alexitimia, sin que necesariamente exista associación entre ellas; 2. la cualidad de la adaptación no presenta asociación con la severidad de la sintomatología, ni con el tiempo de la enfermedad; 3. la alexitimia se mostró negativamente asociada a La gravedad de los síntomas gastrointestinales pero no con el tiempo de la enfermedad. Investigaciones con muestras más representativas son sugeridas.

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)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.297
GPT teacher head0.545
Teacher spread0.247 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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