A Hybrid Approach for Evaluating Environmental Impacts for Urban Transportation Mode Sharing
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
The current paper presents an AHP based approach for evaluating sustainable transport solution measures like car-sharing, park and ride, access control zones etc. In the first stage, we identify the indicators (criteria) for evaluating the transportation solution measure. These indicators (criteria) can be divided into several sub-indicators (sub-criteria). In the second stage, we allot weights to the indicators and sub-indicators using AHP. The values for the sub-indicators are measured using multiple sources and multiplied with their weights in order to compute state change variable values that form part of the city state equation. The respective values of the state change variables in the city state equation are then used to evaluate the efficiency of the transportation solution measure. Finally, we illustrate our approach by giving an example of car-sharing and measuring its impact on city environmental conditions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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