A blockchain-based user-centric emission monitoring and trading system for multi-modal mobility
Bibliographic record
Abstract
A new design of a user-centric Emission Trading Systems (ETS) and its implementation as a carbon Blockchain framework for Smart Mobility Data-market (cBSMD) is pre-sented. The cBSMD allows for individual transactions of token-based GHG emission quantities when realizing a trip in a multimodal setting as well as the management of system-wide emission performance data. The cBSMD design is here applied to an ETS framework where individual travellers receive a certain amount of emission credits in the form of tokens. Travellers spend tokens every time they emit GHG when travelling in a multi-modal network through cBSMD transactions. This design instance of cBSMD is then applied to a case-study of 24hours of mobility for 3,187 travelers. The cBSMD performs with a very low latency and high throughput for this number of travelers. To showcase cBSMD data management features, socio-demographic and trip features regarding token usage and emission performance are also analyzed. Our proposed system sets the first implementation step towards the design of future user-centric and practice-ready ETS frameworks.
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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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".