Стан інтеграції української ортопедичної науки у світову
Bibliographic record
Abstract
The involvement of Ukrainian clinical scientists in the field of orthopedics and traumatology in world of medicine is an urgent problem, as evidenced by the level of reflection of domestic research in international specialized publications. Objective: to determine the features of scientific activity of Ukrainian orthopedic and traumatology surgeons based on the analysis of quantitative indicators as Scimago Journal & Country Rank, Scopus and Web of Science.Methods: the Hirsch index (h-index, Scopus) of 92 doctors of medical sciences in the specialty «Traumatology and Orthopedics», selected from the «Scientists of Ukraine» database (V. I. Vernadsky National Library), was evaluated. The number of publications of these researchers in foreign journals in general (according to the Scimago Journal & Country Rank) was analyzed. We also estimated the dependence on the quartile of the journal (Web of Science) in the specialty Orthopedics and Sports Medicine from 2014 to 2018.Results: for the studied period of time (2017–2018), the publication activity of Ukrainian doctors was increased in the specialty Orthopedics and Sports Medicine. So, in 2017, Ukraine took the 69th place (Scimago Journal & Country Rank) in terms of the number of publications in the ranking of countries of the world, and in 2018 — already 62nd. More than half of the identified works were published in the journals of the fourth quartile, and only a quarter of the first. The citation index of the most orthopedic traumatology surgeons remains low, which can be explained by the choice of a journal for publication with a low impact factor or a small number of published works indexed by Scopus and Web of Science.Conclusions: it is necessary to introduce Evidence-based medicine research standards into everyday practice. This determines the importance of teaching our native scientists how to plan and conduct research study, analyze and prepare for printing the results.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.010 |
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".