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Record W4394910204 · doi:10.1016/j.cjca.2024.04.009

Navigating the Landscape of Medical Device Advisories: A Special Report From the Canadian Heart Rhythm Society Device Advisory Committee

2024· review· en· W4394910204 on OpenAlexaffvenueabout
Jason G. Andrade, Alice Virani, A. Staunton, Marc Bains, Derek S. Chew, Nathaniel M. Hawkins, Jacqueline Joza, Clarence Khoo, Jaimie Manlucu, François Philippon, Calum J. Redpath, Laurence D. Sterns

Bibliographic record

VenueCanadian Journal of Cardiology · 2024
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsUniversité LavalWestern UniversityLibin Cardiovascular Institute of AlbertaUniversity of OttawaMcGill UniversityRoyal Jubilee HospitalVancouver General HospitalUniversity of CalgaryUniversité de MontréalMontreal Heart InstituteUniversity of British ColumbiaUniversity of ManitobaInstitut universitaire de cardiologie et de pneumologie de QuébecBC Innovation Council
Fundersnot available
KeywordsMedicineHeart RhythmAdvisory committeeRhythmMedical emergencyCardiologyInternal medicineManagement

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.015
metaresearch head score (Gemma)0.030
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: Review · Consensus signal: Review
Teacher disagreement score0.860
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.057
GPT teacher head0.358
Teacher spread0.301 · 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
GenreReview

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

Citations3
Published2024
Admission routes3
Has abstractno

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