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Record W4417033977 · doi:10.15173/m.v1i48.4038

Effectiveness of Repetitive Transcranial Magnetic Stimulation Treatment on Depression

2025· article· W4417033977 on OpenAlexvenueno aff
Ajuni Birak

Bibliographic record

VenueThe Meducator · 2025
Typearticle
Language
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationDepression (economics)Prefrontal cortexDeep transcranial magnetic stimulationDorsolateral prefrontal cortexAdverse effectMajor depressive disorderTranscranial direct-current stimulation

Abstract

fetched live from OpenAlex

Major depressive disorder (MDD) is a prevanlent mental health condition often treated with medication that may cause adverse effects, especially in younger individuals. Repetitive transcranial magnetic stimulation (rTMS) is a promising alternative for those who do not respond to traditional medications and methods of therapy. This noninvasive treatment targets brain regions associated with depression, such as the dorsolateral prefrontal cortex (DLPFC), using magnetic pulses to modulate neural activity. Current studies show that rTMS can improve response and remission rates with fewer side effects compared to standard treatments. Its safety profile, combined with its effectiveness for treatment-resistant cases, makes it a promising alternative to antidepressants. While current research on rTMS is limited by varying treatment durations and a lack of long-term data, rTMS presents as a valuable option for managing MDD.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.022
GPT teacher head0.315
Teacher spread0.293 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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