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Record W2136925486 · doi:10.1093/ehjci/jes318

2013 European Association Cardiovascular Imaging Research Grants

2013· article· en· W2136925486 on OpenAlexaboutno aff
Rosa Sicari, Thor Edvardsen, Luigi P. Badano, P Lancellotti, Gilbert Habib, Gerald Maurer

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionAssociation (psychology)Order (exchange)Political scienceMedicineLibrary scienceBusinessPsychologyLawComputer scienceFinance

Abstract

fetched live from OpenAlex

Since its beginning, the European Association of Cardiovascular Imaging (formerly European Association of Echocardiography) Research Programme has funded eight grants and allowed the awardees to expand their research interests in outstanding centres in the field of echocardiography in Europe outside their home institution (for a full report, see: Eur Heart J Cardiovasc Imaging 2012;13:47–50). The success of the initiative induced the Board to invest more money and four grants have been funded for the year 2013. The increment of funding with the possibility of higher chances of success increased significantly the applications with the record number of 25. A few changes have been made as regards the application format (which was prepared in a pre-specified format in order to homogenize the detailed description of the project), submission (all documents are now submitted electronically), the way of evaluating the projects by appointment of an independent committee of scientist external to the Board in order to avoid any potential conflict of interest, and the scoring system (20 point overall, 1–5 points for the candidate CV; 1–10 points for the overall project quality, and 1–5 points for the feasibility of the research over a year time span);. The external committee was formed by the following scientists: Otto Smiseth (Oslo, Norway); Erwan Donal (Rennes, France); Mark Monaghan (London, UK); Antonella Moreo (Milan, Italy); Phillippe Pibarot (Quebec, Canada); Gerald Maurer (Wien, Austria); and Jarek Kasprzak, Lodz, Poland).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.007

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 head0.042
GPT teacher head0.306
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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