MétaCan
Menu
Back to cohort
Record W3038500363 · doi:10.1097/yct.0000000000000713

Electroconvulsive Therapy and Triaging During Reduced Access and the COVID-19 Pandemic

2020· article· en· W3038500363 on OpenAlexaffabout
Michael L Demas

Bibliographic record

VenueJournal of Ect · 2020
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsGrey Nuns Community Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Electroconvulsive therapy2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicPsychiatryMedicineWeb siteGrey literatureUniversity hospitalMEDLINELibrary sciencePsychologyFamily medicinePolitical scienceThe InternetInternal medicineWorld Wide WebVirologyComputer scienceLaw

Abstract

fetched live from OpenAlex

From the Psychiatry ECT Program, Grey Nuns Community Hospital, Edmonton, Alberta, Canada. Received for publication April 14, 2020; accepted June 21, 2020. Reprints: Michael L. Demas, MD, Associate Clinical Professor of Psychiatry ECT Program, Unit 17, Rm 1759, Grey Nuns Community Hospital, 1100 Youville Dr W, NW, Edmonton, Alberta, Canada, T6L 5X8 (e-mail: [email protected]). The authors have no conflicts of interest or financial disclosures to report. Supplemental digital contents are available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.ectjournal.com).

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)0.008
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 score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.107
GPT teacher head0.370
Teacher spread0.263 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of EctSame topicElectroconvulsive Therapy StudiesFrench-language works237,207