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Record W2890252655 · doi:10.1016/j.jacc.2018.08.1348

TCT-225 Impact of frailty on a minimalist approach and early discharge following TAVR: insights from the 3M TAVR Study

2018· article· en· W2890252655 on OpenAlexaff
Janarthanan Sathananthan, Sandra Lauck, John A. Cairns, Karin H. Humphries, D. Murdoch, Mark Hensey, Richard Cook, Meijiao Guan, Julie Park, Yinshan Zhao, Robert C. Welsh, Jonathon Leipsic, Danny Dvir, Benjamin D. Tyrrell, Jonathan Afilalo, Faisal Alqoofi, James L. Velianou, Madhu K. Natarajan, Harindra C. Wijeysundera, Sam Radhakrishnan, Eric Horlick, Anita Asgar, Jean‐Bernard Masson, Susheel Kodali, Tamim Nazif, Vinod H. Thourani, Vasilis Babaliaros, David J. Cohen, Martin B. Leon, John Webb, David Wood

Bibliographic record

VenueJournal of the American College of Cardiology · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity of TorontoFoothills Medical CentreUniversity of British Columbia HospitalRoyal Alexandra HospitalMontreal Heart InstituteUniversity of British ColumbiaHealth Sciences CentreVancouver General HospitalCanadian VIGOUR CentreSunnybrook Health Science CentreMcMaster UniversitySt. Paul's Hospital
Fundersnot available
KeywordsMedicineValve replacementCardiologyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.339
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2018
Admission routes1
Has abstractno

Explore more

Same venueJournal of the American College of Cardiology→Same topicCardiac Valve Diseases and Treatments→French-language works237,207→