Навчання в дистанційному синхронному та асинхронному режимах в українських закладах вищої освіти з 2020 року дотепер
Bibliographic record
Abstract
1. Тези Цитуйте у Ванкувер стилі українською: [Шевченко ОС, Шевченко ВВ. Навчання в дистанційному синхронному та асинхронному режимах в українських закладах вищої освіти з 2020 року дотепер. Матеріали Міжнародної науково-практичної конференції «Цифрова трансформація та диджитал технології для сталого розвитку всіх галузeй сучасної освіти, науки і практики» (Міжнародний університет прикладних наук у Ломжі, Польща; Державний біотехнологічний університет, Харків, Україна, 26.01.2023), том 4, с. 98-102. https://doi.org/10.5281/zenodo.7598963]. Ключові слова: навчання під час війни, вища освіта, Україна. 2. Сертифікати учасників конференції 3. Збірка тез 1. Abstract Cite in English in Vancouver style: [Shevchenko AS, Shevchenko VV. Learning in remote synchronous and asynchronous modes in Ukrainian higher education institutions from 2020 until now. International scientific and practical conference proceedings "Digital transformation and technologies for all areas sustainable development of modern education, science and practice" (International University of Applied Sciences in Lomza, Poland; State Biotechnological University, Kharkiv, Ukraine, 26 Jan 2023). Publishing house: MANS w Łomży, Lomza, Poland, 2023. Part 4. P. 98-102. https://doi.org/10.5281/zenodo.7598963 (in Ukrainian)]. Keywords: education during the war, higher education, Ukraine. 2. Certificates of conference participants 3. Abstract's book: [Digital transformation and technologies for sustainable development all branches of modern education, science and practice [Electronic resource]: International Scientific and Practical Conference Proceeding, January 26, 2023 / Edited by I. Zuchowski, Z. Sharlovych, O. Mandych / International Academy Applied Sciences in Lomzа (Poland) - State Biotechnological University (Ukraine). – Publishing house: MANS w Łomży, Lomza, Poland, 2023. Part 4. 106 p.]
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.020 |
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".