CONSIDERATION OF THE CASE ON THE RECOVERY OF COMPENSATION FOR VIOLATION OF THE EXCLUSIVE COPYRIGHT THROUGH THE PRISM OF MATRIX GAMES
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
Abstract: the article reveals the conditions for applying the matrix games toolkit to situations with legal content. Using the example of case no. A40-162373/2020 on the recovery of compensation for infringement of exclusive copyright, the compilation of the “profitability” matrix is demonstrated. Using the Bayes, Wald, Savage and Hurwitz criteria the optimal strategy of legal behavior of the copyright holder and the violator is mathematically justified. It is shown that predicting the outcome of a civil dispute using these criteria will allow the participants of the turnover to determine the strategy of legal behavior in the absence of a unified approach in law enforcement practice and minimize their own costs.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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