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Record W4282946998 · doi:10.1016/j.brs.2022.06.005

Does switching between high frequency rTMS and theta burst stimulation improve depression outcomes?

2022· letter· en· W4282946998 on OpenAlexaboutno aff
Leo Chen, Elizabeth Thomas, Pakin Kaewpijit, Aleksandra Miljevic, Lisa Hahn, Alexandra Lavale, Kate E. Hoy, Cherrie Galletly, Paul B. Fitzgerald

Bibliographic record

VenueBrain stimulation · 2022
Typeletter
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationStimulationAntidepressantRandomized controlled trialDepression (economics)Prefrontal cortexPsychologyBrain stimulationScopusNeuroscienceMajor depressive disorderDorsolateral prefrontal cortexMedicinePsychiatryInternal medicineMEDLINEMoodChemistryHippocampus

Abstract

fetched live from OpenAlex

We read with interest recent articles in Brain Stimulation, reporting on the antidepressant effects of theta burst stimulation (TBS) applied in accelerated schedules [1,2] and the efficacy comparison between unilateral and bilateral repetitive transcranial magnetic stimulation (rTMS) approaches [3]. We recently reported a multisite randomized controlled trial comparing the antidepressant efficacy of accelerated bilateral TBS applied at 80% or 120% of the resting motor threshold (RMT) and left-sided 10 Hz rTMS applied at 120% RMT [4].

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)0.004
metaresearch head score (Gemma)0.026
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: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.032
GPT teacher head0.288
Teacher spread0.256 · 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
GenreCommentary

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
Published2022
Admission routes1
Has abstractyes

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