EFEKTIFITAS APLIKASI KONVENSI TOKYO 1963 DAN PROTOKOL MONTREAL 2014 TERHADAP UNRULY PASSENGER CASE DALAM DUNIA PENERBAGANGAN
Bibliographic record
Abstract
Peraturan yang berlaku di dalam pesawat penerbangan dimaksudkan agar masyarakat mematuhi hal-hal apa saja yang harus dan tidak boleh dilakukan ketika berada dalam pesawat penerbangan. Peraturan yang sudah ada ini tak terlepas dari pelanggaran terhadap aturan yang berlaku di dalam pesawat. Kasus penumpang yang tidak mematuhi aturan atau dikenal dengan unruly passenger merupakan sebuah contoh pelanggaran terhadap aturan yang berlaku di dalam pesawat. Konvensi Tokyo 1963 menjadi jawaban dalam mengatasi kasus unruly passenger tersebut. Namun, kandungan dari Konvensi Tokyo 1963 pada kenyataannya belum mampu menangani seluruh masalah terkait unruly passenger. Melihat hal tersebut, ICAO mengamandemen Konvensi Tokyo 1963 untuk memperkuat dasar hukum bagi maskapai dalam menangani kasus unruly passenger, hingga akhirnya menghasilkan Protocol to Amend the Convention on Offences and Certain Other Acts Committed on Board Aircraft atau dikenal sebagai Protokol Montreal 2014. Keberadaan Konvensi Tokyo 1963 dan Protokol Montreal 2014 ini diharapkan mampu mengatasi permasalahan terkait unruly passenger dalam dunia penerbangan.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.005 |
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".