Bibliographic record
Abstract
This article is dedicated to the anniversary of geophysicist, doctor of physical and mathematical sciences, Professor Yuri Pavlovich Neprochnov, who would turn 90 years old this year. Prof. Neprochnov created a school of seismic marine geologists. He had numerous students, who prepared and successfully defended 12 Ph.D., and D.Sc. dissertations under his leadership. He is the author and co-author of more than 400 scientific articles and 18 monographs. Neprochnov was a Member of the Second World War, a Member of the Scientific Council of the Russian Academy of Sciences on the problems of the oceans, where he led the working group on seismic and integrated geophysics; Coordinator of International projects for scientific cooperation with India, China and Finland, a Member of the Editorial board of the Journal «Oceanology», was elected a full Member of the Russian Academy of Natural Sciences and a Member of the New York Academy of Sciences, and in 2002 for his labor successes and a great contribution to strengthening friendship and cooperation between peoples he was awarded the title of Honored Scientist of the Russian Federation. His friend and colleague in scientific geophysical research L.I. Kogan recalls years of teamwork and expresses his appreciation for professional friendships throughout his life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".