The Congenital Heart Surgeons' Society Presidents and Their Contributions
Bibliographic record
Abstract
The Congenital Heart Surgeons’ Society (CHSS) was founded by 16 congenital heart surgeons in 1973, who endeavored to share their clinical advances in an informal setting that would stimulate honest and forthright discussions. As the Society grew, prospective studies were organized from a centralized data center that was established and based first in Birmingham, Alabama, thence to Toronto, and recently in a collaboration between Toronto and the Cleveland Clinic. These studies formed the basis for a myriad of outcomes reports that favorably impacted surgical results. The Kirklin–Ashburn Fellowship was created and endowed by the membership which has been successful in training many congenital heart surgeons. The CHSS was then incorporated into a 501(c) (3) not-for-profit organization with bylaws, officers, and committees in 2002. Increased membership followed. The CHSS has become the face of congenital heart surgery in North America by affiliating with the World Journal for Pediatric and Congenital Heart Surgery, having one designated member on the American Board of Thoracic Surgery, and hosting joint meetings with the European Congenital Heart Surgeons Association. Since 2002, 11 presidents have been elected for two-year terms and have guided the advances that have been achieved by the CHSS. Their contributions and achievements are highlighted in chronological order.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".