Context‐sensitive, first‐principles approach to bicycle speed estimation
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
Bicycle speed estimation is important for geometric design, traffic signal operations, microsimulation models, and health and safety assessment, among other applications. Bicycle speeds can vary greatly with the characteristics and power output of the rider and with travel conditions, especially road grade. This study presents a mathematical framework to address the non‐trivial and practical problem of estimating bicycle free‐flow speeds in a way that is sensitive to cyclist and roadway attributes. A closed expression is derived from first principles to determine speed from bicyclist power output. The method is extended to the problem of speed estimation for bicycles with limited gearing. Results are consistent with speed surveys in the literature. Application of the method to clearance interval calculation demonstrates the importance of context‐sensitive bicycle speed estimation for advanced traffic signal systems.
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 | 0.000 | 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 it