INTERNATIONAL MEDICAL FORUM “UKRAINIAN AND GLOBAL MEDICINE: BASICS, REALITY, AND STRATEGIC PROSPECTS”
Bibliographic record
Abstract
From December 13 to 15, 2023, the International Medical Forum (IMF) “Ukrainian and Global Medicine: Basics, Reality, and Strategic Prospects” was held successfully. Within the framework of this forum, the 12th Christmas Readings on Immunology and Allergology were held. The event was dedicated to the 150th anniversary of the Shevchenko Scientific Society (SSS), the 125th anniversary of the Medical Commission of the SSS, and the 25th anniversary of the Department and Center of Clinical Immunology and Allergology. Event hosts were the Medical Commission of the Shevchenko Scientific Society and Danylo Halytsky Lviv National Medical University. Despite difficult times for Ukraine, the event did not lose its leadership positions in terms of the number of speeches and the diversity of the agenda, and the vast geography of speakers and specialist attendees distinguished it. More than 400 speakers, about 1,000 listeners, and more than 1,200 online participants participated in the event. During three days, international experts from the USA, Canada, UK, Italy, Spain, Denmark, Slovakia, Sweden, Germany, Austria, and Poland, and leading scientists and experts for Ukraine delivered more than 300 speeches.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".