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Record W3007396459

Tabaquisme i addicció a la nicotina. Relació amb el dolor de difícil control i l’edmonton classification system for cancer pain (ecs-cp)

2016· dissertation· ca· W3007396459 on OpenAlex
Jaume Canals Sotelo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTDX (Tesis Doctorals en Xarxa) · 2016
Typedissertation
Languageca
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
Fundersnot available
KeywordsCatalanHumanitiesArtPhilosophyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Catala.Objectiu: Realitzar la traduccio i la validacio linguistica al Catala i al castella de la “Quick Users Guide” de l’ Edmonton Classification System for Cancer Pain (ECS-CP). Metodologia: A partir de la traduccio de l’original i amb el proces de retrotraduccio i conciliacio linguistica es va obtenir una versio en catala i en castella. L’estudi de llegibilitat es va fer mitjancant l’Index de Llegibilitat de Flesch-Szigriszt (IFSZ) i l’Index de Fernandez-Huertas. Resultats: Per a les dues versions els resultats van ser d’una mica dificil i apte per a un nivell d’escolaritzacio de batxillerat. L’estudi de fiabilitat mitjancat el coeficient kappa promig va donar un resultat de 0,79 per a la versio catalana i de 0,83 per la castellana, reflexant un grau d’acord bo i molt bo, respectivament. En una mostra de 211 pacients oncologics avancats i fumadors el model multivariant de regressio logistica multiple va mostrar que l’edat 6 punts (addiccio severa a la nicotina) eren factors de risc de presentar dolor amb EVA > 6 (dolor sever). Castella. Objetivo: Realizar la traduccion y la validacion linguistica al catalan y al castellano de la “Quick Users Guide” de l’ Edmonton Classification System for Cancer Pain (ECS-CP). Metodologia: A partir de la traduccion del original y a traves de un proceso de retrotraduccion y de conciliacion linguistica se obtuvieron una version en catalan y otra en castellano. El estudio de legibilidad se realizo mediante el Indice de Legibilidad de Flesch-Szigriszt (IFSZ) y el Indice. Resultados: Para las dos versiones el resultado fue de un poco dificil y apto para una poblacion con nivel de escolarizacion de bachillerato. El estudio de fiabilidad mediante el coeficiente kappa promedio dio el resultado de 0,79 per a la version catalana y de 0,83 para la castellana, reflejando un grado de concordancia bueno y muy bueno, respectivamente. En una muestra de 211 pacientes oncologicos avanzados y fumadores el modelo multivariante de regresion logistica mostro que la edad 6 puntos (adiccion severa a la nicotina) eran factores de riesgo de presentar dolor con una EVA > 6 (dolor severo). Angles. Objectives: To translate and to validate the “Quick Users Guide” of Edmonton Classification System for Cancer Pain (ECS-CP) into Catalan and Spanish. Method: From the original translation and following a back-translation process and grammatical adaptation a version in both Catalan and Spanish languages was obtained. The readability study was carried out by using the Flesch-Szigriszt readability index and the Fernandez-Huertas Index. Results: For both versions the outcome was a bit difficult and according to a high school literacy level. The reliability analysis used the kappa coefficient with an score of 0,79 for the catalan version and 0,83 for the Spanish version, respectively. In a sample of 211 advanced cancer smokers patients the multivariate analysis showed that younger patients (age 6 points (severe nicotine addiction) were the most important risk factors to develop severe pain (VAS>6).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.021
GPT teacher head0.328
Teacher spread0.306 · 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