TO THE ANNIVERSARY OF VOLODYMYR MALASCHENKO
Bibliographic record
Abstract
The article is dedicated to the 85th anniversary of the famous Ukrainian scientist in the field of mechanical engineering and machine dynamics, professor of the department of technical mechanics and engineering graphics of the National University "Lviv Polytechnic", doctor of technical sciences, academician of the Lifting and Transport Academy of Sciences of Ukraine, Volodymyr Oleksandrovych Malashchenko. After the restoration of Ukraine's independence, Volodymyr Oleksandrovych was one of the organizers of the process of training highly qualified specialists. Many of the candidate's and doctoral dissertations were defended under his supervision or opposition, not only in mechanical engineering but also in lifting and transport machines, agriculture, printing, oil and gas engineering. He is the author of more than 600 works, including more than ten monographs, more than 100 patents, about 30 study guides (of which six are in French), and about 20 articles in foreign publications indexed by scientometric databases. Volodymyr Oleksandrovych is also the author of a complex of study guides on machine design, which are widely used in the educational process of almost all technical universities of Ukraine. He is a member of the editorial boards of the magazines "Lifting and Transport Technology", "Bulletin of NTU "KhPI", series of Engineering and CAD", a member of the program and organizational committee of the international scientific and technical conference "Problems of Quality and Durability of Gears and Mechanical Drive".
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.058 | 0.069 |
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".