MétaCan
Menu
← Back to cohort
Record W7036350860

Benefici de l’exercici aeròbic moderat en salut cardiovascular en pacients en hemodiàlisi: Assaig clínic controlat i randomitzat: (Estudi “Hemovas”)

2019· dissertation· ca· W7036350860 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typedissertation
Languageca
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PopulationMercantilism
DOInot available

Abstract

fetched live from OpenAlex

Pregunta clínica: Un programa d’exercici físic aeròbic intradiàlisi durant 18 setmanes tindria beneficis en la salut cardiovascular en pacients amb hemodiàlisi crònica? \nObjectiu: Analitzar l’efecte d’exercici físic aeròbic durant 18 setmanes sobre l’estat cardiovascular en pacients en hemodiàlisi. \nMetodologia: Assaig clínic controlat randomitzat que recollirà un total de 70 pacients amb malaltia renal crònica amb hemodiàlisi. Es randomitzaran en dos grups, el grup A serà el grup control i el grup B serà l’intervingut i cada grup estarà format per 35 pacients. \nA tots els pacients se’ls farà una valoració basal, al mig de la intervenció i al final de les 18 setmanes (Visita 0- 1- 2). Al grup A (control) s’aplicarà solament tractament convencional, és a dir, hemodiàlisi. Al grup B, s’aplicarà la hemodiàlisi i l’exercici físic aeròbic durant tres dies a la setmana, durant 25 min durant la sessió de hemodiàlisi. \nLes dades es recolliran a través de les eines metodològiques següents: La tensió arterial i la freqüència cardíaca els resultats es recolliran a través del tensiòmetre. Les dades de la rigidesa arterial a través de la velocitat d’ona de pols amb l’aparell Arteriograph. I les dades del perfil lipídic i nutricional amb una extracció de sang.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.267
Teacher spread0.259 · 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 designRandomized trial
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicTrauma and Emergency Care Studies→French-language works237,207→