Інноваційні розробки безпілотних авіаційних систем Національного авіаційного університету
Bibliographic record
Abstract
1. Dmytro Bugayko, Volodymyr Kharchenko, Marek Foriash New Technologies in the Global Aero — Space Engineering Education Logistics and Transport- Wroclaw: International School of Logistics and Transport in Wroclaw. — 2014.-№ 4(24).-P. 37-44. \n2. Unmanned Aircraft Systems /Сire. ICAO 328 — AN/190. — Canada, Montreal: ICAO, 2011.-325 p. \n3. Joint Unmanned Aircraft Systems Minimum Training Standards: — Guidance / Joint Staff Washington D.C. -2012.-32 p. \n4. Луцький M. Г., Харченко В. П., Бугайко Д. О. Розвиток міжнародного регулювання та нормативної бази використання безпілотних літальних апаратів. Вісник НАУ. - К.: НАУ, 2011. - Ns 2. - С. 5-14. \n5. V. Kharchenko, D. Bugayko, М. Paw?ska, D. Prusov. The Efficiency and Effectiveness of Remotely Piloted Aircraft Systems Used in Logistics Problems Solving Due to Territorial Infrastructure. Logistics and Transport - Wroclaw: International School of Logistics and Transport in Wroclaw. - 2014. - № 2(22). - P. 13-20. \n6. V. Kharchenko, D. Bugayko, Wang Bo. Fundamentals of Safety and Efficiency of the Next Genefation Unmanned Aircraft Systems. Proceedings the six World Congress «Aviation in the XXI-st century», «Safety in Aviation and Space Technologies», 23-25 sept. 2014, Kyiv / NAU. - Kyiv, 2014. - V. 2. - P.2.29-2.35. \n7. https://nau.edu.ua/ua/news/2020/gruden/dp-derzhavne-kiivske-konstruktorske- byuro-luchvisloviv-shchiru-vdyachnist-natsionalnomu-aviatsiynomu-universitetu.html
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".