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Record W2613494736 · doi:10.1016/j.hrthm.2017.03.038

2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry

2017· article· en· W2613494736 on OpenAlexafffund
Jonathan S. Steinberg, Niraj Varma, Iwona Cygankiewicz, Peter F. Aziz, Paweł Balsam, Adrián Baranchuk, Daniel J. Cantillon, Polychronis Dilaveris, Sérgio Dubner, Nabil El‐Sherif, Jarosław E. Król, Małgorzata Kurpesa, Maria Teresa La Rovere, S. Suave Lobodziński, Suneet Mittal, Brian Olshansky, Ewa Piotrowicz, Leslie A. Saxon, Peter H. Stone, Larisa G. Tereshchenko, Gioia Turitto, Neil J. Wimmer, Richard L. Verrier, Wojciech Zaręba, Ryszard Piotrowicz

Bibliographic record

VenueHeart Rhythm · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsQueen's University
FundersCleveland ClinicUniversity of RochesterUniwersytet WarszawskiSUNY Downstate Medical CenterBoston Scientific CorporationUniwersytet ŁódzkiWarszawski Uniwersytet MedycznyNational and Kapodistrian University of AthensState University of New YorkBiosense WebsterNational Institutes of HealthFondazione Salvatore MaugeriQueen's UniversityPfizer
KeywordsMedicineAmbulatoryClinical PracticeTelemetryIntensive care medicineAmbulatory ECGCardiologyInternal medicineComputer sciencePhysical therapy

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)0.029
metaresearch head score (Gemma)0.058
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 score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.058
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0050.002
Science and technology studies0.0020.002
Scholarly communication0.0050.003
Open science0.0050.005
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0090.009

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 head0.032
GPT teacher head0.323
Teacher spread0.291 · 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

Citations291
Published2017
Admission routes2
Has abstractno

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