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Hypertrophic Cardiomyopathy: A Review Using Magnetic Resonance Imaging

2022· review· pt· W4312186211 on OpenAlex

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

VenueARQUIVOS BRASILEIROS DE CARDIOLOGIA - IMAGEM CARDIOVASCULAR · 2022
Typereview
Languagept
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicineHypertrophic cardiomyopathyCardiac magnetic resonanceMagnetic resonance imagingCardiologyRadiology

Abstract

fetched live from OpenAlex

A cardiomiopatia hipertrófica é a cardiopatia genética mais frequente na população geral e é caracterizada por uma hipertrofia ventricular esquerda assimétrica. Entretanto, as alterações fenotípicas desta cardiomiopatia vão muito além da hipertrofia ventricular, e incluem alterações do aparato valvar mitral, dos músculos papilares e do ventrículo direito. Devido à dificuldade no diagnóstico diferencial entre as múltiplas causas de hipertrofia, a ressonância magnética cardíaca vem cumprindo um papel fundamental na avaliação diagnóstica e prognóstica desta cardiomiopatia. A cineressonância magnética na definição da localização e extensão da hipertrofia, o realce tardio, na detecção das áreas de fibrose miocárdica e técnicas mais recentes como o Mapa de T1 que avalia a fibrose intersticial e o volume extracelular; e finalmente o Tissue Tracking na análise da deformação miocárdica.

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)0.014
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.005
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0230.034
Bibliometrics0.0010.004
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0030.004
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0010.001

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 head0.304
Teacher spread0.247 · 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