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Record W2330715457 · doi:10.1093/europace/eus035

'Pathways for training and accreditation for transvenous lead extraction: a European Heart Rhythm Association position paper' [Europace 2012;14:124-134. doi: 10.1093/europace/eur338]

2012· article· en· W2330715457 on OpenAlexaboutno aff
Jean‐Claude Deharo, Maria Grazia Bongiorni, A. Rozkovec, Frank Bracke, Pascal Defaye, Ignacio Fernández Lozano, Pier Giorgio Golzio, Bert Hansky, Charles Kennergren, Antonis S. Manolis, Przemysław Mitkowski, Eivind S. Platou

Bibliographic record

VenueEP Europace · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart RhythmAccreditationAssociation (psychology)CardiologyMedical educationPsychotherapist

Abstract

fetched live from OpenAlex

The names of the EHRA reviewers were inadvertently omitted from the paper. The following reviewer names should have been included: Andreas Löher (Germany), Milos Taborsky (Czech Republic), Antonio Curnis (Italy), and Marc Dubuc (Canada).

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)0.068
metaresearch head score (Gemma)0.113
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.113
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0080.006
Open science0.0070.005
Research integrity0.0200.011
Insufficient payload (model declined to judge)0.0240.011

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 head0.063
GPT teacher head0.315
Teacher spread0.252 · 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
GenreOther

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

Citations17
Published2012
Admission routes1
Has abstractyes

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