Practice of the Appeal Board of the Federal Antimonopoly Service (Russia) (Scientific review of the most significant cases examined in the fourth quarter of 2019)
Bibliographic record
Abstract
Ratio of regional antimonopoly`s decisions appealed under collegial body of the Federal antimonopoly service related to the establishment of the facts of the conclusion of prohibited competition-restricting agreements exceeds the part of the other decisions. In most cases, this is related to the issues of proving the arrangement and implementation of competition-restricting agreement, because not always certain circumstances can clearly indicate the fact of conclusion of such agreement. The most interesting are the cases of «bid rigging» cartels, which are prohibited by paragraph 2 of the part 1 of article 11 of the Federal law "On protection of competition" (hereinafter — the Law on protection of competition). Establishing that competitionrestricting agreements in each case, all collected in the case on violation of Antimonopoly legislation of the evidence to be assessed, without which it is impossible to make an informed decision on the case, and defendants in cases usually do not agree with the competition authority of certain evidence as proof of anti-competitive agreements.
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.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".