Bibliographic record
Abstract
UNCITRAL Working Group on Electronic Commerce held an extensive discussion on issues related to electronic contracting and prepared and revised the UNCITRAL draft convention on contracts concluded or evidenced by data message. the UNCITRAL draft convention on contracts concluded or evidenced by data message. would seem to be focused to achieve the legal certainty and predictability which may arise electronic commerce. The purpose of this paper is to raise the understanding of the convention on the electronic contracting and the related contract law by studying the contents of Draft Convention on Electronic Contracting. This study is regarding the contract law with applying UNCITRAL draft convention on contracts concluded or evidenced by data message. UNCITRAL has prepared the draft to provide the legal framework to help facilitate e-commerce. Based on the Vienna convention made in 1980. this draft reflected the UNCITRAL model law on electronic commerce, UNCITRAL model law on electronic signatures, UETA of US and UECA of Canada. This draft doesn't separate electronic contracts from non-electronic contracts by the objects of trade. but it defines electronic contracts made by the methods of trades, in other words, data message. The draft doesn't deal with such problems as ambiguity, disagreement in interpretation or resolving disputes between the parties in contracts. The draft should be subject to review, discussion and approvals of countries, before becoming unified international laws on electronic contracts.
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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 | 0.025 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".