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Record W2787342342 · doi:10.7759/cureus.2174

Sleep Deprivation Therapy Enhanced Via Repetitive Transcranial Magnetic Stimulation in Major Depression

2018· review· en· W2787342342 on OpenAlexaff
Abhishek Gupta

Bibliographic record

VenueCureus · 2018
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsTranscranial magnetic stimulationMedicineDepression (economics)Sleep deprivationMajor depressive disorderPsychiatryDeep transcranial magnetic stimulationNeurosciencePhysical medicine and rehabilitationStimulationMoodPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (rTMS) and sleep deprivation (SD) are two of the latest advances made in the field of psychiatric research. Though yet in development, they present unique opportunities to achieve significant clinical outcomes particularly in major depression disorder (MDD). A limited set of studies have been done in the combined use of rTMS-SD in treating MDD. While promising, these studies have been hampered by the limited knowledge of rTMS and SD themselves due to their relatively recent use as viable therapeutic options. This review is aimed at an analysis of the limitations observed in the studies conducted to date involving rTMS and SD. In addition, it explores the potential new avenues for future research in the deployment of rTMS-SD as a viable treatment option.

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 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 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 score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.342
Teacher spread0.274 · 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 teacher head, not a consensus.

Study designOther design
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

Citations4
Published2018
Admission routes1
Has abstractyes

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