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Record W2945486426 · doi:10.15420/cfr.2018.41.2

Aortic Stenosis and Heart Failure: Disease Ascertainment and Statistical Considerations for Clinical Trials

2019· review· en· W2945486426 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

VenueCardiac failure review · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité Laval
FundersBoston Scientific CorporationEdwards Lifesciences
KeywordsMedicineStenosisHeart failureClinical trialDiseaseQuality of life (healthcare)Heart diseaseAortic valve stenosisCardiologyInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Aortic stenosis is a progressive disease that develops over decades, and once symptomatic and untreated, is associated with poor survival. Transcatheter aortic valve replacement has evolved significantly in the past decade and has expanded its indication from surgically inoperable and high-risk patients to patients with intermediate risk. Assessment of heart failure-related outcomes include the use of functional assessments, disease-specific quality of life surveys and standardised ascertainment of events, such as hospitalisations. Multiple statistical approaches are currently being tested to account for recurrent events such as hospitalisations for heart failure or to combine binary and continuous outcomes, both intended to assess the holistic burden of the disease, as opposed to the traditional analysis of time to first event.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0000.000
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 head0.191
GPT teacher head0.517
Teacher spread0.326 · 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