Multiplicity results for systems of first order dynamic inclusions on time scales
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advances in Continuous and Discrete Models: Theory and Modern Applications is a peer-reviewed open access journal published under the brand SpringerOpen. Computational and applied mathematics along with data science play a vital role in contemporary society by driving innovation. This success can be attributed to revolutionary theoretical and algorithmic developments in machine learning, data driven modeling, differential equations, numerical analysis, scientific computing, control, optimization, and computing resources together with new tools to deal with uncertainty and randomness. This journal encourages new research in these broad areas. In addition to research on algorithmic and analytical developments, the journal also encourages papers related to (but not limited to) broad applications in Signal and Image Processing, Computer Vision, Materials Science, Mathematical Biology and Bioengineering. As a result, the journal will be an excellent connecting bridge between mathematical research and real world applications. The journal accepts high-quality articles containing original research results and survey articles of exceptional merit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it