Thoracic oncology HERMES: European curriculum recommendations for training in thoracic oncology
Bibliographic record
Abstract
The HERMES (Harmonising Education in Respiratory Medicine for European Specialists) project is funded by the European Respiratory Society (ERS) and has the declared aims of harmonising education in thoracic medicine, recognising diplomas and certificates of qualification, and improving free access and mobility for medical specialists across the European Union (EU). This takes into account Directive 2013/55/EU of the European Parliament and of the Council [1] on the recognition of professional qualifications, one of the pillars of EU legislation. Moreover, it conforms to the fact that there is a shortage of medical/surgical specialists in several European countries, which means that more physicians of other European and non-European countries will be needed to sustain the functioning and development of health services in future years and decades [2]. HERMES is working towards the development of harmonised and structured programmes for education across respiratory specialties to ensure that the best care is delivered for those suffering from respiratory diseases. Thoracic oncology HERMES: European curriculum recommendations for training in thoracic oncology The authors affiliations are as follows. F. Gamarra: Division of Respiratory Medicine, Klinikum Straubing, Straubing, Germany. J-L. Noël: European Respiratory Society, Lausanne, Switzerland. A. Brunelli: Dept of Thoracic Surgery, St James’s University Hospital, Leeds, UK. A.-M.C. Dingemans: Dept of Pulmonology, Maastricht University Medical Centre, Maastricht, Netherlands. E. Felip: Hospital Universitari Vall d’Hebron, Barcelona, Spain. M. Gaga: 7th Respiratory Medicine Dept, Athens Chest Hospital, Athens, Greece. B.D. Grigoriu: University of Medicine and Pharmacy, Regional Institute of Oncology, Iasi, Romania. G. Hardavella: Dept of Respiratory Medicine, King’s College Hospital, London, UK, and University College London, Lungs for Living Research Centre, London, UK. R.M. Huber: Division of Respiratory Medicine and Thoracic Oncology, Thoracic Oncology Centre Munich, University of Munich, Munich, Germany. S. Janes: Centre for Respiratory Research, University College London, London, UK. G. Massard: Dept of Thoracic Surgery, University of Strasbourg, Strasbourg, France. P.M. Putora: Dept of Radio-oncology, Kantonsspital St. Gallen, St. Gallen, Switzerland. J-P. Sculier: Intensive Care and Thoracic Oncology, Institut Jules Bordet, Brussels Belgium. P.A. Schnabel: Institut für Allgemeine und Spzielle Pathologie, Saarland University, Homburg/Saar, Germany. S. Ramella: Dept of Radiation Oncology, Campus Bio-Medico University, Rome, Italy. D. Van Raemdonck: Dept of Thoracic Surgery, University Hospitals Leuven, Leuven, Belgium. A-P. Meert: Dept of Intensive Care and Thoracic Oncology, Institut Jules Bordet, Brussels, Belgium. We would like to thank the ERS Leadership, Gernot Rohde (Education Council Chair) and Ernst Eber (HERMES Director), as well as the medical education specialists Erik Driessen and Griet Peeraer. We would also like to thank Sharon Mitchell and Alexandra Niculescu (European Respiratory Society), the ERS Thoracic Oncology Assembly, Dirk de Ruysscher and Jesper Grau Eriksen (European Society for Radiotherapy and Oncology), and Rolf Stahel Rainer Wiewrodt (European Society for Medical Oncology). We would also like to thank the following national respondents: M. Nanushi (Albania), S. Taright (Algeria), H. Marshall (Australia), K. Kirchbacher (Austria), O. Burghuber (Austria), K.N. Uglyanitsa (Belarus), L. Bosquee (Belgium), M. Bakir (Bosnia/Herzegovina), M. Zamboni (Brazil), A. Kousoulova (Bulgaria), I. Novakov (Bulgaria), N. Bouchard (Canada), V. Ivcevic (Croatia), J. Skrikova (Czech Republic), J. Skrickova (Czech Republic), T.R. Rasmussen (Denmark), T. Laisaar (Estonia), J. Jaal (Estonia), R. Makitaro (Finland), M. Wislez (France), F. Barlesi (France), T. Blum (Germany), E. Stoelben (Germany), K. Gourgouliannis (Greece), J. Moldvay (Hungary), S. Jonsson (Iceland), A. Mohan (India), R. Morgan (Ireland), M. Kennedy (Ireland), Y. Schwarz (Israel), S. Elia (Italy), M. Beishembaev (Kyrgyzstan), A. Krams (Latvia), E. Danila (Lithuania), M. Schlesser (Luxembourg), S. Brincat (Malta), K. Skaug (Norway), J. Domagala-Kulawik (Poland), R. Sotto Mayor (Portugal), D. Jovanovic (Republic of Serbia), C. Paleru (Romania), D. Jovanovic (Serbia), P. Bezinec (Slovakia), E. Kavcova (Slovakia), N. Triller (Slovenia), I. Alfageme (Spain), G. Hillerdal (Sweden), L. Wannesson (Switzerland), S. Burgers (The Netherlands), H.J.M. Groen (The Netherlands), A. Erbaycu (Turkey), N. Lukavetskyy (Ukraine), P. Beckett (UK), M. Peake (UK), L. Kamman (USA) and O. Ioachimescu (USA).
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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.028 |
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".