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Record W4394841735 · doi:10.2459/jcm.0000000000001616

Management of hypertrophic cardiomyopathy

2024· article· en· W4394841735 on OpenAlex
Yuhui Zhang, Marianna Adamo, Changhong Zou, Aldostefano Porcari, Daniela Tomasoni, Maddalena Rossi, Marco Merlo, Huihui Liu, Jinxi Wang, Ping Zhou, Marco Metra, Gianfranco Sinagra, Jian Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cardiovascular Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsHypertrophic cardiomyopathyMedicineCardiologySudden cardiac deathSudden deathCardiomyopathyHeart failureIntensive care medicineInternal medicineHemodynamicsEpidemiology

Abstract

fetched live from OpenAlex

Hypertrophic cardiomyopathy is an important cause of heart failure and arrhythmias, including sudden death, with a major impact on the healthcare system. Genetic causes and different phenotypes are now increasingly being identified for this condition. In addition, specific medications, such as myosin inhibitors, have been recently shown as potentially able to modify its symptoms, hemodynamic abnormalities and clinical course. Our article aims to provide a comprehensive outline of the epidemiology, diagnosis and treatment of hypertrophic cardiomyopathy in the current era.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.267
Teacher spread0.250 · 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