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Record W3216079554 · doi:10.1016/j.brs.2021.10.521

Use of the Virtual Brain to target networks in treatment resistant depression

2021· article· en· W3216079554 on OpenAlexaff
Sora An, Jan Fousek, Zelma H. T. Kiss, Filomeno Cortese, Gwen van der Wijk, Laina McAusland, Rajamannar Ramasubbu, Viktor Jirsa, Andrea B. Protzner

Bibliographic record

VenueBrain stimulation · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDepression (economics)Treatment-resistant depressionNeurosciencePsychologyMedicineMajor depressive disorderCognitionEconomics

Abstract

fetched live from OpenAlex

contrast, p40 amplitude was a poor predictor of cingulum bundle perturbation (p¼.18).Contrary to our hypothesis, results showed a similar pattern for the p100 feature, which was associated with forceps minor (r 2 ¼.77, p<.01) rather than cingulum bundle (p¼.07).Exploratory analyses reveal an earlier midline feature that appears more specific to the cingulum bundle.We conclude that EP features may provide an index of stimulation effects on key fiber bundles associated with treatment efficacy to guide optimal DBS parameter selection for individual patients.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.060
GPT teacher head0.289
Teacher spread0.229 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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