国際委員会企画 JACS-ASCVTS Joint Session
Bibliographic record
Abstract
A trailblazer in thoracoscopic surgery, Professor Jheon has led multicenter studies in Korea, published approximately 250 papers, and founded the educational program for Asian young surgeons, which has trained over 500 surgeons.He is an active member of numerous medical societies, including serving as the president of the Asian Society of Cardiovascular and Thoracic Surgery.In 2011, he initiated the Asian Thoracoscopic Surgery Education Platform, which has since evolved into the Asian Thoracic Academy.Since 2010, Professor Jheon has spearheaded innovations at Seoul National University Bundang Hospital, earning the Most Respected Hospital CEO Award in Korea in 2019.Recently, Professor Jheon has been focused on integrating cutting-edge technologies such as ICT, XR, and Metaverse into healthcare.He founded Health-on-Cloud and the Smart Hospital Alliance, with groundbreaking projects like the Metaversity/Cloud Hospital Platform and Medi-Tech Exchange Platform currently being trialed in Asia and Latin America.His innovative mindset is fostering positive change in the healthcare landscape.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.077 | 0.038 |
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".