Bibliographic record
Abstract
In May 2022, I received an email from Tristan Yan, Editor of Annals of Cardiothoracic Surgery (ACS), inviting me to be the guest editor of an issue of his journal dedicated to aortic valve sparing operations (AVS) because it had been 30 years since the first peer-reviewed publication on this topic (1). Since I was attending the 2022 Techno Praticum College meeting organized by Homayoun Jalali in July in Sydney, I proposed that we meet in person to discuss the contents of this special issue of the ACS. A few hours after arriving in Sydney I met my friend and former clinical fellow Gebrine El Khoury, an early adopter of AVS. I told him about Tristan's proposal and asked him to be my co-guest editor. He accepted and with the indispensable assistance of Jama Jahanyar, one of Gebrine's associates, in less than a month we had enough topics to fill two issues of the ACS. Tristan Yan accepted our request for a second issue to better cover all aspects of AVS.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".