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The night‐eating syndrome and obesity

2012· review· en· W2157157752 on OpenAlexaff
A. R. Gallant, J. Lundgren, Vicky Drapeau

Bibliographic record

VenueObesity Reviews · 2012
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsObesityContext (archaeology)Circadian rhythmMoodWeight gainDistressPopulationMedicineEating disordersWeight lossInsomniaPsychologyPsychiatryClinical psychologyBody weightEnvironmental healthInternal medicineBiology

Abstract

fetched live from OpenAlex

The rising prevalence of obesity is a global concern. Eating behaviour and circadian rhythm are proving to be important factors in the aetiology of obesity. The night-eating syndrome (NES) is characterized by increased late-night eating, insomnia, a depressed mood and distress. It is evident that prevalence is higher among weight-related populations than the general community. The exact relationship between this syndrome and obesity remains unclear. The reasons for the discrepancies found in the literature likely include varying diagnostic criteria and a wide range of study population characteristics. NES does not always lead to weight gain in thus certain individuals may be susceptible to night-eating-related weight gain. Weight loss through surgical and behavioural treatments has shown success in diminishing symptoms. The increasing literature associating obesity with circadian imbalances strengthens the link between the NES and obesity. Circadian genes may play a role in this syndrome. This review will examine different aspects of obesity in the context of the NES.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.104
GPT teacher head0.324
Teacher spread0.220 · 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

Citations182
Published2012
Admission routes1
Has abstractyes

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