Target Pencapaian Rencana Umum Keselamatan Jalan (RUNK Jalan) di Provinsi Jawa Timur pada Tahun 2012
Bibliographic record
Abstract
Jawa Timur merupakan provinsi tertinggi dalam jumlah korban meninggal dunia (4575 jiwa)akibat kecelakaan lalulintas dalam tahun 2010. Dalam tahun 2011 ternyata jumlah kecelakaanmeningkat, mengapa? Rupanya target RUNK jalan (Rencana Umum Nasional Keselamatan)belum tercapai karena belum diterapkan. Mungkin hal ini disebabkan oleh karena belum adanyasosialisasi yang efektif tentang RUNK sehingga pihak pengatur belum menerapkan RUNK secaraterkoordinir dan selaras, dan pengguna jalan masih kurang sadar bahayanya kecelakaan dijalan danbelum waspada dalam berlalu lintas. Berdasarkan analisis data yang terkumpul dalam pelatihancara menghitung target RUNK, dengan menggunakan lima parameter analisis, yaitu jumlahkejadian kecelakaan, tingkat kecelakaan, tingkat fatalitas (CFR), indeks fatalitas per kendaraanbermotor dan indeks fatalitas per populasi, ternyata beberapa kota dan kabupaten mempunyai datajumlah korban fatal yang tinggi, diatas nilai rata-rata RUNK dan secara umum kondisi kecelakaanlalulintas tahun 2011 lebih jelek dari kondisi tahun 2010.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".