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Record W7028010798

EFECTIVIDAD DE LA ACTIVIDAD FÍSICA MAS DIETA SALUDABLE EN LA DISMINUCIÓN DE PESO EN ADULTOS CON SOBREPESO Y/O OBESIDAD.

2020· dissertation· es· W7028010798 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2020
Typedissertation
Languagees
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightWeight lossPhysical activityObesityRandomized controlled trialSystematic reviewSedentary lifestyleBody mass index
DOInot available

Abstract

fetched live from OpenAlex

Objective: Systematize evidence on effectiveness of physical activity plus healthy diet in weight loss in overweight and/or obese adults; establish effective recommendations to avoid overweight in adults.Materials and Methods: The 10 scientific articles in this systematic review of the effectiveness of physical activity plus healthy diet in weight loss in overweight and/or obese adults have been found in databases: Scielo 10%, PubMed 20%, Cochrane 70% all high evidence studies, such as systematic reviews and meta-analysis with 80%, randomized controlled trials with 20%.Coming from countries such as Chile 10%, Norway 10%, Canada 10%, Japan 10%, Spain 10% and United States 50%.The revised studies show recommendations to prevent overweight in adults such as decreasing sugar use, salt, boosting fiber intake in food, practicing sports that incentivize physical movement and decrease sedentary overweight.Results: 100% of the articles in this systematic review show that healthy diet and physical activity are most effective in weight loss in overweight and/or obese adults.Conclusion: The 10 reviewed articles state that healthy diet and physical activity are most effective in weight reduction in overweight and/or obese adults, as these separate activities will delay body weight reduction.

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)0.007
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.016
GPT teacher head0.396
Teacher spread0.380 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venuerenatiSame topicHealth and Lifestyle StudiesFrench-language works237,207