United Mexican States <i>v</i>. Feldman Karpa
Bibliographic record
Abstract
536 Arbitration — Challenge — Arbitration tribunal constituted under North American Free Trade Agreement (“NAFTA”), Chapter 11 — Arbitral award — Mexico applying to set aside arbitral award — Proceedings in Canadian courts Arbitration — Disclosure of confidential information — Adverse inference from failure to provide information — Article 34 of UNCITRAL Model Law — NAFTA Article 2105 Relationship of international law and municipal law — Application for judicial review of arbitral award — Annulment of award by national court — Article 34 of UNCITRAL Model Law — Jurisdiction to apply provisions not raised during arbitral proceedings — NAFTA Article 210 — Deference to arbitral award — International commercial arbitrators — Review of findings of fact — Article 34(2) and 34(3) of UNCITRAL Model Law — ICSID Article 53 — Breach of public policy — Article 34(2) (b)(ii) of UNCITRAL Model Law Economics, trade and finance — Investment protection — NAFTA — Chapter 11 — National treatment — Nondiscrimination — NAFTA Article 1102 — Less favourable treatment of foreign investors — The law of Canada
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.120 | 0.021 |
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".