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Record W4223921139 · doi:10.1002/ehf2.13929

Therapeutic Inertia in the Pharmacological Management of Heart Failure with Reduced Ejection Fraction

2022· editorial· en· W4223921139 on OpenAlexaboutno aff
Nicolas Girerd, Jean‐Jacques Von Hunolstein, Pierpaolo Pellicori, Antoni Bayés‐Genís, Tiny Jaarsma, Lars H. Lund, Pascal Bilbault, Jean‐Marc Boivin, Tahar Chouihed, Jérôme Costa, Jean‐Christophe Eicher, Estelle Fall, David Kénizou, B Maillier, Pierre Nazeyrollas, G Roul, N. Zannad, Patrick Rossignol, Marie‐France Seronde

Bibliographic record

VenueESC Heart Failure · 2022
Typeeditorial
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGeneral hospitalUniversity hospitalLibrary scienceEmergency medicine

Abstract

fetched live from OpenAlex

Girerd, Nicolas; Von Hunolstein, Jean-Jacques; Pellicori, Pierpaolo; Bayés-Genís, Antoni; Jaarsma, Tiny; Lund, Lars H.; Bilbault, Pascal; Boivin, Jean-Marc; Chouihed, Tahar; Costa, Jérôme; Eicher, Jean-Christophe; Fall, Estelle; Kenizou, David; Maillier, Bruno; Nazeyrollas, Pierre; Roul, Gérald; Zannad, Noura; Rossignol, Patrick; Seronde, Marie-France

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)0.012
metaresearch head score (Gemma)0.037
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 score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.301
Teacher spread0.285 · 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

Citations51
Published2022
Admission routes1
Has abstractyes

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