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Record W4401961208 · doi:10.1002/ejhf.3412

The Right Heart in Patients with Cancer. A Scientific Statement of the Heart Failure Association (HFA) of the ESC and the ESC Council of Cardio-Oncology

2024· article· en· W4401961208 on OpenAlexaff
Kalliopi Keramida, Dimitrios Farmakis, Amina Rakisheva, Carlo G. Tocchetti, Pietro Ameri, Riccardo Asteggiano, Ana Barac, Jeroen J. Bax, Antoni Bayés‐Genís, Jutta Bergler Klein, Chiara Bucciarelli‐Ducci, Jelena Čelutkienė, Andrew J.S. Coats, Alain Cohen Solal, Susan Dent, Gerasimos Filippatos, Arjun K. Ghosh, Joerg Hermann, Yvonne Koop, Daniel J. Lenihan, Teresa López‐Fernández, Alexander R. Lyon, Valentina Mercurio, Brenda Moura, Massimo Piepoli, Yusuf Ziya Şener, Thomas Suter, Aaron L. Sverdlov, Marijana Tadić, Thomas Thum, Peter van der Meer, Sophie Van Linthout, Marco Metra, Giuseppe Rosano

Bibliographic record

VenueEuropean Journal of Heart Failure · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
FundersServierCilagAstellas PharmaNovo NordiskEisaiCytokineticsAmicus TherapeuticsImpulse DynamicsFondation LeducqGilead SciencesNational Heart Foundation of AustraliaBeiGeneDaiichi Sankyo EuropeEuropean CommissionSanofiAmgenVifor PharmaMinistero della SalutePfizerUniversitair Medisch Centrum GroningenAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineFamily medicineLibrary scienceInternal medicine

Abstract

fetched live from OpenAlex

2077

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 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations17
Published2024
Admission routes1
Has abstractyes

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