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Record W2232112941 · doi:10.1016/j.jcmg.2015.10.016

Abnormal Lymphatic Channels Detected by T2-Weighted MR Imaging as a Substrate for Ventricular Arrhythmia in HCM

2016· letter· en· W2232112941 on OpenAlexafffund
Louis Kolman, Donald G. Welsh, Edward J. Vigmond, Sebastien X Joncas, John Stirrat, David Scholl, Martin Rajchl, Edward Tweedie, Yoko Mikami, Carmen Lydell, Andrew G. Howarth, Raymond Yee, James A. White

Bibliographic record

VenueJACC. Cardiovascular imaging · 2016
Typeletter
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsFoothills Medical CentreWestern UniversityHôtel-Dieu de QuébecRobarts Clinical TrialsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHypertrophic cardiomyopathyCardiologyInternal medicineMedicineMagnetic resonance imagingMyocardial fibrosisCardiac magnetic resonanceCardiomyopathyCardiac magnetic resonance imagingSudden cardiac deathFibrosisRadiologyHeart failure

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)0.001
metaresearch head score (Gemma)0.007
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 score0.012
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0120.007
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.230
Teacher spread0.221 · 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

Citations16
Published2016
Admission routes2
Has abstractno

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