Екологічні фактори ризику серцево-судинних захворювань
Bibliographic record
Abstract
Цитуйте українською у стилі Ванкувер: [Огнєв ВА, Піонтковська ОВ, Черняк МЄ, Шевченко ОС. Екологічні фактори ризику серцево-судинних захворювань. Матеріали ХXХІ Міжнародної науково-практичної конференції "Інформаційні технології: наука, техніка, технологія, освіта, здоров'я" (MicroCAD-2023), 17–20 тра 2023, НТУ "ХПІ", Харків, Україна. C. 366. https://doi.org/10.5281/zenodo.7970297] Cite in English in Vancouver style: [Ohniev VA, Piontkovska OV, Cherniak MIe, Shevchenko AS. Environmental risk factors for cardiovascular diseases. Proceedings of the XXXI International scientific and practical conference "Information technologies: science, technology, technology, education, health" (MicroCAD-2023), NTU "KhPI", Kharkiv, Ukraine, 17–20 May 2023. P. 366. https://doi.org/10.5281/zenodo.7970297 (in Ukrainian)] Abstract book & full conference program: https://doi.org/10.5281/zenodo.7949461
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.025 |
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".