ANALISIS POLA PERGERAKAN LAYANAN \nTRANSPORTASI ONLINE DI KAWASAN \nUNIVERSITAS DIPONEGORO \n
Bibliographic record
Abstract
Kawasan kampus Universitas Diponegoro (UNDIP) memiliki perkembangan \ndan Perencanaan yang pesat. Akan tetapi Perencanaan yang dilakukan kurang \ndirencanakan dengan baik sehingga menimbulkan kawasan sprawl. Dikarenakan \nkondisi Perencanaan yang sprawl tersebut menyebabkan transportasi publik yang \ntersedia menjadi sulit menjangkau antar kawasan. Oleh karena itu terjadi kesenjangan \nantara kebutuhan dan ketersediaan (demand and supply) akan sarana transportasi \npublik. Dalam permasalahan tersebut muncul sebuah inovasi transportasi berbasis \nteknologi informasi, yaitu transportasi online. \n
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".