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Record W2772327035 · doi:10.1177/2045125317743435

Neuromodulation for the treatment of eating disorders and obesity

2017· review· en· W2772327035 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

VenueTherapeutic Advances in Psychopharmacology · 2017
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsEating disordersNeuromodulationDeep brain stimulationObesityMedicineAnorexia nervosaQuality of life (healthcare)Transcranial direct-current stimulationAnorexiaPsychiatryClinical trialManagement of obesityPsychologyPsychotherapistWeight lossDiseaseStimulationInternal medicineParkinson's disease

Abstract

fetched live from OpenAlex

Eating disorders and obesity adversely affect individuals both medically and psychologically, leading to reduced life expectancy and poor quality of life. While there exist a number of treatments for anorexia, morbid obesity and bulimia, many patients do not respond favorably to current behavioral, medical or bariatric surgical management. Neuromodulation has been postulated as a potential treatment for eating disorders and obesity. In particular, deep brain stimulation and transcranial non-invasive brain stimulation have been studied for these indications across a variety of brain targets. Here, we review the neurobiology behind eating and eating disorders as well as the current status of preclinical and clinical neuromodulation trials for eating disorders and obesity.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.111
GPT teacher head0.498
Teacher spread0.387 · 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