Bibliographic record
Abstract
ABB 411-12 absence of a right of contribution 581 abuse of dominance 555 accomplishment theory 392-3 accrual 214 acquis communautaire 414 action or omission by allegedly liable party (Spain) 390 actori incumbit probatio principle 323 adequacy 133-4, 137, 254 of notice 269-71 of representation test 130-31, 376 adjudicatory costs 427 adjustment by benefi t 341 admission 174 Advanced Micro Devices 65-8 aff ected parties (Germany) 332-3 affi rmative acts standard 217 Africa see Asia and Africa after the event insurance 313 AGC 77, 81 Agent Orange 230-32 aggregation of claims 33, 124-40, 604-5 Australia 491-2 Canada 453-4 common case leadership 126-8 consolidation of cases 124-6 England and Wales 303-6 Federal Trade Commission disgorgement claims 140 France 321-3 Germany 335-6 India 510-11 Italy 363-6 Korea 545-6 mass actions 138-9 Netherlands 370-71 'opt-out' cases 137-8 parens patriae cases 139 Taiwan 565-6 Turkey 420 see also class actions seeking damages; group proceedings; representative actions agricultural cooperatives/associations 62, 80, 149 Air Cargo 22, 121-2 Air-Insulated Switchgear 22 Airline Deregulation Act 80 airline industry 80
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.814 | 0.727 |
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".