Al-Hwaidi in the Law and Practice of Documentary Letters of Credit
Bibliographic record
Abstract
Functional comparative study in the law and practice of documentary letters of credit and analysis of UCP 600, ISBP and ICC Opinions Decisions of English, Jordanian and Egyptian courts and some legislations and courts decisions of American, Singaporean, Canadian, Australian, Chinese, French and German Laws Translation in Arabic for ISBP 2013 تحليل فقهي ودراسة مقارنة للقانون والقضاء والفقه في الاعتمادات المستندية وفي تحليل نشرة الأعراف والعادات الموحدة (النشرة 600) والمعيار الدولي وآراء غرفة التجارة الدولية قرارات محكمة التمييز الأردنية وقرارات محكمة النقض المصرية وقرارات المحاكم الإنجليزية وبعض تشريعات وقرارات المحاكم في القانون الأمريكي والسينغافوري والكندي والأسترالي والصيني والفرنسي والالماني دراسة تجريبية للأعراف والعادات التجارية للإعتمادات المستندية ترجمة في اللغة العربية للمعيار الدولي للأصول المصرفية لفحص المستندات في الاعتمادات المستندية 2013
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".