Quantifying and classifying the robustness of bus transit networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study adopts Complex Network Theory in the context of bus transit network. The study aims at quantifying the topological characteristics and assessing the validity of static-robustness metrics as expressive measures of transit networks robustness. In addition, dynamic-robustness indices, that consider transit operational profile, are utilized to measure the cascading impacts of disruptive events. The analysis is based on a dataset of 40 bus transit networks. The results indicate that bus networks don't conform to any major network class: scale-free, small-world, or random. Furthermore, the static-robustness metrics produced contradictory results, which raises valid concerns on their applicability. The dynamic-robustness indices developed in the current study indicated significant cascading impacts resulting from node removal relative to the removal of links. This behaviour was further examined through a two-step cluster analysis, which resulted in three distinct network clusters: small node-sensitive; small link-sensitive; and medium less-sensitive networks. These findings are directed to inform a robustness-based design of bus transit networks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it