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Record W2068483637 · doi:10.1093/ehjci/jeu192

Expert consensus for multimodality imaging evaluation of adult patients during and after cancer therapy: a report from the American Society of Echocardiography and the European Association of Cardiovascular Imaging

2014· article· en· W2068483637 on OpenAlexaff
Juan Carlos Plana, Maurizio Galderisi, Ana Barac, Michael S. Ewer, Bonnie Ky, Marielle Scherrer‐Crosbie, Javier Gáname, Igal A. Sebag, Deborah A. Agler, Luigi P. Badano, José Banchs, Daniela Cardinale, Joseph R. Carver, M. Cerqueira, Jeanne M. DeCara, Thor Edvardsen, Scott D. Flamm, Thomas Force, Brian P. Griffin, Guy Jérusalem, J. E. Liu, Andreia Magalhães, Thomas H. Marwick, Liza Sanchez, Rosa Sicari, Hector R. Villarraga, Patrizio Lancellotti

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsMcGill UniversityJewish General HospitalMcMaster University
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineMultimodalityCardiac imagingRadiologyMedical imagingPositron emission tomographyInternal medicineMedical physics

Abstract

fetched live from OpenAlex

administration. We recognize that in the setting of a variety of predisposing factors, varying cumulative dosages of recognized cardiotoxic agents, and use of other agents that are known to increase oxidative stress and compromise myocyte stability, the algorithm proposed in this document cannot be based on strong clinical data.

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)0.040
metaresearch head score (Gemma)0.052
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0050.004
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0020.003

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 head0.278
Teacher spread0.263 · 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
GenreOther

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

Citations1,052
Published2014
Admission routes1
Has abstractyes

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