Mankowski's Commercial Law - Article-by-Article Commentary
Bibliographic record
Abstract
Effective cross-border trade depends on reliable rules and legal certainty. However, cross-border trade is a complex undertaking, not limited only to sales, but also encompassing carriage and transport, finance, and marketing. Accordingly, a clear understanding of the legislation underpinning the major areas of commercial law is absolutely essential for successful international commerce. Written in English by a team of international experts, the second edition of this leading Commentary contains revised and updated article-by-article analyses of: Convention on Contracts for the International Sale of Goods (CISG) Convention on the Limitation Period in the International Sale of Goods (LPC) UNIDROIT Principles of International Commercial Contracts (PICC) Incoterms© 2020 Convention on the Contract for the International Carriage of Goods by Road (CMR) COTIF Uniform Rules Concerning the Contract of International Carriage of Passengers (CIV) and Goods (CIM) Convention for the Unification of Certain Rules for International Carriage by Air (Montreal Convention) Budapest Convention on the Contract for the Carriage of Goods by Inland Waterway (CMNI) EU Commercial Agents Directive 86/653 EU Late Payment Directive 2011/7 Convention on International Interests in Mobile Equipment (Cape Town Convention) Uniform Customs and Practices for Documentary Credits (UPC 600)
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".