Demarcation of Territorial Boundaries in International Lawand Procedure: Technical Factors Role
Bibliographic record
Abstract
Technological advances in any domain effects other domains as well. International law and especially international boundaries take advantage of technical progresses orconsidering the factors which existed before but they have been neglected and put these factors in the service of its demands. Maybe if we consider each of the technical factors separately, we cannot understand their role properly in boundarydomains, but we study their setting in the form of boundaries demarcation and consider the package generally and investigate the relationship of internal factors. It is clear that technical factors have developed a great evolution in demarcation of territorial boundaries.Eventually, when the technical parameters are employed for demarcation of territorial boundaries, in fact they serve to its purpose; the purpose is nothing than maintaining international peace, order and security, the fact that is the existential philosophy of the United Nations organization. Thus, non-human factors have been served for human factors and maintain its values. Definitely next advances in technical factors will be along with other developments in boundaries domain.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.050 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".