Bibliographic record
Abstract
IMIA Member Societies and Corresponding Members Member Societies AMIA (American Medical Informatics Association) Argentine Association of Medical Informatics (AAIM) Association for Health Informatics of Nigeria (AHIN) Association for Medical and Bio-Informatics, Singapore (AMBIS) Association for Medical Informatics of Serbia Belgian Medical Informatics Association Brazilian Society of Health Informatics (SBIS) British Computer Society (BCS Health) Burundi Health Informatics Association Cameroonian Health Informatics Society (CAHIS) Chilean Health Informatics Society China Medical Informatics Association COACH: Canada’s Health Informatics Association Colombian Association for Health Informatics Croatian Society for Medical Informatics Cuban Society of Medical Informatics Czech Society for Biomedical Engineering and Medical Informatics eHealth Association of Pakistan (eHAP) Finnish Social and Health Informatics Association (FinnSHIA) French Medical Informatics Association (AIM) German Association for Medical Informatics, Biometry and Epidemiology (GMDS) Ghana Health Informatics Association Greek Health Informatics Association Health Informatics New Zealand Health Informatics Society of Australia Ltd. (HISA) Health Informatics Society of Sri Lanka Healthcare Informatics Society of Ireland Hong Kong Society of Medical Informatics Indian Association for Medical Informatics (IAMI) Iranian Medical Informatics Association Ivorian Society of Biosciences and Health Informatics (ISBHI) Japan Association for Medical Informatics John von Neumann Computer Society (Hungary) Kenya Health Informatics Association Korea Society of Medical Informatics (KOSMI) Medical Informatics Association of Malawi (MIAM) Mexican Medical Informatics Association Norwegian Society for Medical Informatics Peruvian Association of Biomedical Informatics Philippine Medical Informatics Society Romanian Society of Medical Informatics Slovenian Medical Informatics Association (SIMIA) Society for Medical Informatics of Bosnia and Herzegovina South African Health Informatics Association Spanish Society of Health Informatics Swedish Federation for Medical Informatics (SFMI) Swiss Society for Medical Informatics Taiwan Association for Medical Informatics (TAMI) Thai Medical Informatics Association The Bolivian Medical Informatics and Telemedicine Society (SOBOTIM) The Israeli Association for Medical Informatics (ILAMI) The Mali Society of Biomedical and Health Information (SOMBIS) The Saudi Association for Health Informatics (SAHI) The Ukrainian Association for Computer Medicine (UACM) Togolese Association for Medical Informatics and Telemedicine (ATIM-TELEMED) Turkish Medical Informatics Association (TURKMIA) Uruguayan Society of Health Informatics Venezuelan Association of Computer Science in Health (AVIS) VMBI, Society for Healthcare Informatics (The Netherlands) Working Group Medical Informatics and eHealth of the Austrian Computer Society (OCG) and the Austrian Society for Biomedical Engineering (ÖGBMT) # Corresponding Members Albania, Algeria, Armenia, Azerbaijan, Bangladesh, Democratic Republic of Congo, Egypt, El Salvador, Indonesia, Iraq, Jamaica, Jordan, Kuwait, Lebanon, Madagascar, Malaysia, Moldova, Nepal, Oman, Qatar, Russian Federation, Sudan, Syria, Tanzania, Trinidad & Tobago, Uganda, United Arab Emirates, Uzbekistan, Zambia, Zimbabwe # Affiliate Members International Federation for Information Processing (IFIP) - www.ifp.org International Federation of Health Information Management Associations (IFHIMA) - www.ifhima.org World Health Organization - www.who.int #
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".