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Record W2100391099 · doi:10.3389/fnins.2013.00177

Metabolic disturbances connecting obesity and depression

2013· review· en· W2100391099 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Neuroscience · 2013
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsObesityDepression (economics)Adipose tissueMoodAnxietyEndocrinologyAbdominal obesityMedicineInternal medicineMood disordersDiseasePsychologyBioinformaticsPsychiatryMetabolic syndromeBiology

Abstract

fetched live from OpenAlex

Obesity markedly increases the odds of developing depression. Depressed mood not only impairs motivation, quality of life and overall functioning but also increases the risks of obesity complications. Abdominal obesity is a better predictor of depression and anxiety risk than overall adipose mass. A growing amount of research suggests that metabolic abnormalities stemming from central obesity that lead to metabolic disease may also be responsible for the increased incidence of depression in obesity. As reviewed here, a higher mass of dysfunctional adipose tissue is associated with several metabolic disturbances that are either directly or indirectly implicated in the control of emotions and mood. To better comprehend the development of depression in obesity, this review pulls together select findings addressing the link between adiposity, diet and negative emotional states and discusses the evidence that alterations in glucocorticoids, adipose-derived hormones, insulin and inflammatory signaling that are characteristic of central obesity may be involved.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.316
Teacher spread0.262 · 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