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Record W2409545147 · doi:10.1177/2150135115604840

History of the Congenital Heart Surgeons’ Society

2015· article· en· W2409545147 on OpenAlexaff
Constantine Mavroudis, William G. Williams

Bibliographic record

VenueWorld Journal for Pediatric and Congenital Heart Surgery · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineHeart defectGeneral surgeryHeart diseaseIntensive care medicineSurgeryCardiology

Abstract

fetched live from OpenAlex

The Congenital Heart Surgeons' Society is a group of over 100 pediatric heart surgeons representing 72 institutions that specialize in the treatment of patients with congenital heart defects. The Society began in 1972 and incorporated as a not-for-profit charitable organization in 2004. It has become the face and voice of congenital heart surgery in North America. In 1985, the Society established a data center for multicenter clinical research studies to encourage congenital heart professionals to participate in improving outcomes for our patients. The goals of the Congenital Heart Surgeons' Society are to stimulate the study of congenital cardiac physiology, pathology, and management options which are instantiated in data collection, multi-institutional studies, and scientific meetings. Honest and open discussion of problems with possible solutions to the challenges facing congenital heart professionals have been the strength of the Congenital Heart Surgeons' Society. It is imperative for the growth of an organization to know from where it came in order to know to where it is going. The purpose of this article is to review the history of the Congenital Heart Surgeons' Society.

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)0.003
metaresearch head score (Gemma)0.009
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: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.005
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0120.003

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 head0.073
GPT teacher head0.244
Teacher spread0.171 · 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
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

Citations8
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal for Pediatric and Congenital Heart SurgerySame topicMedical History and InnovationsFrench-language works237,207