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Record W2411796116 · doi:10.1024/0040-5930.57.8.516

Reducing body weight with physical activity and diet – how much is enough and is it possible to lose too much?

2000· review· de· W2411796116 on OpenAlexaff
Doucet

Bibliographic record

VenueTherapeutische Umschau · 2000
Typereview
Languagede
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWeight lossObesityBody weightMedicinePhysical activityGerontologyEndocrinologyPhysical therapy

Abstract

fetched live from OpenAlex

Viele Hinweise deuten darauf hin, dass durch kombinierte therapeutische Maßnahmen (Ernährung und körperliche Aktivität) ein Gewichtsverlust induziert und auch eine Gewichtsstabilisierung erleichtert werden kann. Durch körperliche Aktivität wird vor allem aber auch eine weitgehende Normalisierung des metabolischen Profils erreicht. Liegt «metabolische Fitness» vor, dann ist eine weitere Gewichtsreduktion nur selten gerechtfertigt und kann sogar ungünstig sein für die Gewichtsstabilisierung sowie andere Gesundheitsrisiken, auch wenn das betreffende Individuum nach wie vor als übergewichtig klassifiziert wird.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.044
GPT teacher head0.330
Teacher spread0.285 · 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
GenreReview

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
Published2000
Admission routes1
Has abstractyes

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