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Record W7100946843

Original Research Electroconvulsive Therapy Training in Canada: A Call for Greater Regulation

2015· article· en· W7100946843 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsManiaElectroconvulsive therapyMoodDepression (economics)Bipolar disorderAnxietyMood stabilizer
DOInot available

Abstract

fetched live from OpenAlex

convulsive therapy (ECT) should be considered for all forms of moderate-to-severe depression that are unresponsive to pharmacologic treatment (1). To treat bipolar disorder, the Canadian Network for Mood and Anxiety Treatment (CAN-MAT) guidelines state that ECT should be the first-line treat-ment for acute mania and mixed-mood states that are characterized by severe behavioural disturbances; it is also the recommended treatment option in either partial responders or nonresponders in rapid-cycling bipolar disorder (2). Further, the APA guidelines for the treatment of bipolar disorder state that ECT is indicated as a treatment for medication nonre-sponders in acute mania (3). Moreover, it is a first-line treat-ment for the following: acute mania in pregnancy, neuroleptic malignant syndrome, catatonia, and general medical condi-938

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)0.007
metaresearch head score (Gemma)0.018
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: none
Teacher disagreement score0.929
Threshold uncertainty score0.518

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0390.003

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 head0.209
GPT teacher head0.393
Teacher spread0.184 · 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
Published2015
Admission routes1
Has abstractyes

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