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Record W4285310732 · doi:10.36660/abchf.20220026

Long-Term Ventricular Assist Devices: Where are We in Brazil?

2022· article· en· W4285310732 on OpenAlexaff
Silvia Moreira Ayub‐Ferreira, Bruno Biselli

Bibliographic record

VenueABC Heart Failure & Cardiomyopathy · 2022
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicineHeart failureRefractory (planetary science)Ventricular assist deviceQuality of life (healthcare)Circulatory systemIntensive care medicineCardiologyInternal medicineMaterials science

Abstract

fetched live from OpenAlex

The use of long-term ventricular assist devices (VADs) as a therapeutic option in patients with advanced heart failure (HF) refractory to drug therapy is well established worldwide. The latest update of the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) reported more than 27,000 VAD implants between 2010 and 2019, with approximately 3,000 implants annually in recent years. In addition, 12-month survival rates after implantation reached 82%, with significantly improved quality of life and functional capacity. The technological development of [...]

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 teacher head, not a consensus.

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

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