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Record W1593368544 · doi:10.2174/157340309789317913

Surgical Ventricular Restoration: An Operation to Reverse Remodeling - Clinical Application (Part II) (Supplementry Table)

2009· article· en· W1593368544 on OpenAlexaff
Ganesh Shanmugam, Imtiaz S. Ali

Bibliographic record

VenueCurrent Cardiology Reviews · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Structural Anomalies and Repair
Canadian institutionsHealth Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineVentricular functionSurgical proceduresVentricular remodelingCardiologyMedical physicsSurgeryHeart failure

Abstract

fetched live from OpenAlex

The first part of the article dealt with the basic science behind the evolution of ventricular restoration procedures and the rationale for the use of novel surgical techniques. The second part describes the preoperative workup of patients in advanced heart failure, the core information required to determine the surgical approach and the essential principles and techniques of ventricular restoration. It then examines the effects of ventricular restorative procedures on pump function and clinical outcomes, the results of the worldwide experience with ventricular restoration and concludes with more recent advances in this field.

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)0.000
metaresearch head score (Gemma)0.001
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: Dataset · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.010

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 head0.075
GPT teacher head0.407
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

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
GenreDataset

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

Citations5
Published2009
Admission routes1
Has abstractyes

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