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Record W2810843931 · doi:10.1177/2150135118775962

History of the World Society for Pediatric and Congenital Heart Surgery: The First Decade

2018· article· en· W2810843931 on OpenAlexaffabout
Jeffrey P. Jacobs, Christo I. Tchervenkov, Giovanni Stellin, Hiromi Kurosawa, Constantine Mavroudis, Marcelo Biscegli Jatene, Zohair Al‐Halees, Sertaç Çïçek, Néstor Sandoval, Carl L. Backer, Jorge Cervantes, Joseph A. Dearani, Tjark Ebels, Frank Edwin, Kirsten Finucane, José Fragata, Krishna Iyer, Robin H. Kinsley, James K. Kirklin, Christián Kreutzer, Jinfen Liu, Bohdan Maruszewski, James D. St. Louis, George E. Sarris, Richard A. Jonas

Bibliographic record

VenueWorld Journal for Pediatric and Congenital Heart Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsMedicineExcellenceHeart diseaseHeart defectCardiac surgeryPediatricsGeneral surgeryFamily medicineSurgeryCardiology

Abstract

fetched live from OpenAlex

The World Society for Pediatric and Congenital Heart Surgery (WSPCHS) is the largest professional organization in the world dedicated to pediatric and congenital heart surgery. The purpose of this article is to document the first decade of the history of WSPCHS from its formation in 2006, to summarize the current status of WSPCHS, and to consider the future of WSPCHS. The WSPCHS was incorporated in Canada on April 7, 2011, with a head office in Montreal, Canada. The vision of the WSPCHS is that every child born anywhere in the world with a congenital heart defect should have access to appropriate medical and surgical care. The mission of the WSPCHS is to promote the highest quality comprehensive cardiac care to all patients with congenital heart disease, from the fetus to the adult, regardless of the patient's economic means, with an emphasis on excellence in teaching, research, and community service.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.270
Teacher spread0.241 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

Explore more

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