Bibliographic record
Abstract
proportionality test, 236 single-product test, 511 technological integration, 562, 564 see also Tying American Bar Association, 434, 445 Asian financial crisis, 459, 482 Australia predatory pricing, 635 Belgium electricity sector, 609 emissions trading scheme, 33±34 fiscal state aid, 379±80 Block exemptions motor vehicle distribution, 145±46 sea transport, 111±23 Bundling, 228, 585±93 Canada merger efficiencies balancing weights approach, 265±66, 285±86, 294 Competition Act, 261±62, 266, 285, 287 evidence, 292±97 experts, 290±91 Hillsdown standard, 281±82 merger specificity, 288±89 productive efficiencies, 273±74 R & D efficiencies, 275 redistributive efficiencies, 271±72 Superior Propane, 263±66, 282±87, 289±91, 294, 296±97 total surplus standard, 264±65, 283 predatory pricing, 635 Cartels export, 5±9, 429±31, 450±51 hardcore, 142, 153, 428, 433, 449 international, 101±06, 409, 414±15, 428 CEE countries abuse of dominance enforcement, 247, 249±57 predatory pricing, 252 competition laws, 245±47 regulatory agencies, 248±49, 253 technical assistance, 246±47 Central Europe see CEE countries Community Patent, 15 Competition authorities see National competition authorities Competition policy international cooperation, 4 trade liberalisation, 5, 10 Consumer protection, 16 Consumer switching costs, bundling, 585±93 cases, 575±76 definition, 572 network effects, 580±82 Pareto efficiency, 577±78
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.839 | 0.802 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".