Activities of the Maritime Institute of Russian State Hydrometeorological University
Bibliographic record
Abstract
The authors review the history of the Maritime Institute of the Russian State Hydrometeorological University (St. Petersburg, Russia), which was established in 2005 and headed by S.V. Lukyanov. During this period, the Institute’s specialists have implemented more than 40 research projects in the fields of applied oceanology, including engineering surveys for the design and construction of seaports in the seas of northwestern Russia. The predecessor was the Polar University, founded in 1998 and supported by grants of the “Integration” federal target program and the co-founders — the Russian State Hydrometeorological University and the Arctic and Antarctic Research Institute (AARI). These activities resulted in the creation of a series of devices, such as “Vektor”, “Priliv”, etc. (the inventor was R.A. Balakin ) and as well as the establishment of the collective use center “Marine Technologies” together with the Ministry of Defense of the Russian Federation. This Center served as the basis for the formation of the Interuniversity Base of Student Practice together with St. Petersburg State University and the publication of a series of textbooks (21 titles) for the study of sea ice prepared by AARI scholars. These activities were strictly consistent with the training curricula of oceanology students. Eleven training courses on the Additional Curriculum of the Polar University were created and successfully implemented. At the same time, the Maritime Institute was established exclusively for solving applied scientific problems, with the students being occasionally involved as technicians and given the opportunity to use the data obtained for their diploma projects. The results of the above activities are presented in project reports, numerous scientific publications, diploma projects, collective monographs, as well as in the dissertation works of candidates of sciences and one doctoral dissertation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.011 |
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".