Bibliographic record
Abstract
treatments, were included in the present Research Topic.The collection consists of 14 articles written by a total of 88 Authors from six countries (Canada, China, Germany, Iran, Spain and Switzerland) on three different continents. To date there have already been almost 13,000 total views. Personally, I am particularly fond of the Case Reports sections of surgical Journals because they often include interesting and innovative contributions. The clinical presentation, diagnostic process and effective surgical treatment of rare conditions offer the reader stimulating food for thought. Sometimes there are reported cases of failure but of great educational value. However, Case Reports sections are increasingly rare nowadays in scientific Journals where more value is placed on large-scale studies such as multicenter studies, randomized controlled trials or meta-analyses. For all these reasons, and to give clear objectives and more relevance to Case Reports sections, Frontiers has introduced these regular collections of original surgical cases. I think this editorial initiative is worthy and, personally, I am flattered by the invitation to coordinate it. Both for Heart Surgery and Interventional Cardiology, the most advanced frontiers of the disciplines are often glimpsed by analyzing Case Reports! Very current issues are addressed in the present collection. These issues can be summarized as follows:-The growing importance of minimally invasive surgery and interventional techniques and technologies (1,3,5,14), and of their complications [1,3,14]; -The essential need to carefully plan the surgical strategy before operation [1,6,8,12]; -The essential need of a multimodal imaging for complex lesions [1,3,6,7,8,10,12,13];-The need to develop specific surgical techniques for the treatment of infective endocarditis [11]; -The unusual presentations of "usual" lesions or complications following traditional heart surgery [2,4,7,9,10,12,13].I synthesized the main message of each contribution to the present collection in Table 1.To conclude, I would like to sincerely thank all the valuable Reviewers and Co-editors who helped me in my task. I have certainly learned a lot from them throughout this experience.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.015 |
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".