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Record W4286790088 · doi:10.1002/ehf2.14076

Impact Analysis of Heart Failure Across European Countries: An ESC-HFA Position Paper

2022· review· en· W4286790088 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

VenueESC Heart Failure · 2022
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsHeart failureMedicinePosition (finance)Position paperCardiologyInternal medicineEconomicsPathology

Abstract

fetched live from OpenAlex

Heart failure (HF) is a long-term clinical syndrome, with increasing prevalence and considerable healthcare costs that are further expected to increase dramatically. Despite significant advances in therapy and prevention, mortality and morbidity remain high and quality of life poor. Epidemiological data, that is, prevalence, incidence, mortality, and morbidity, show geographical variations across the European countries, depending on differences in aetiology, clinical characteristics, and treatment. However, data on the prevalence of the disease are scarce, as are those on quality of life. For these reasons, the ESC-HFA has developed a position paper to comprehensively assess our understanding of the burden of HF in Europe, in order to guide future policies for this syndrome. This manuscript will discuss the available epidemiological data on HF prevalence, outcomes, and human costs-in terms of quality of life-in European countries.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.202
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.031
GPT teacher head0.364
Teacher spread0.333 · 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