Bibliographic record
Abstract
It is generally recognized by FRA, AREMA, Amtrak, OSHA, and many other applicable authorities that the maximum acceptable rate of radial acceleration for passengers comfort is 0.1g, where ‘g’ is 9.81 m/s/s. Jerk is limited to 0.03g/s. In the industry the maximum allowable speed (km/h) is calculated by: Vmax=(Ea+Eu′)R11.8 where Eu′ = Blanket unbalance usually greater than design unbalance (mm); Ea = Actual superelevation applied to track (mm); R = Curve radius (m). Clearly the purpose of the equation is to achieve a gain in speed with using the existing spiral at the cost of the comfort limit. It appears that there is a consensus in breaking the standard comfort limit. The value of blanket unbalance varies from operator to operator e.g. 65mm, 75mm, 100mm etc. This variation indicates that there is no consensus in an upper limit beyond standard passenger comfort limit to determine the maximum allowable speed. This is the main reason behind the variation of unbalance, Eu′ adopted by different railways. Other minor reasons are ability of the vehicle to negotiate unbalance, strength of track to withstand lateral load, maintenance standard of track etc. Current use of blanket unbalance superelevation for all types of curves is flawed because it leads to different values of jerk depending on design speed, radius, and incremental unbalance on top of design unbalance. Among these different values of jerk, all values may not be acceptable. The current practice of using a blanket unbalance superelevation may not generate the maximum allowable speed. Intuitively the actual and unbalance superelevation should vary together such that a higher unbalance should go with higher actual superelevation to ensure a consistent comfort. Thus the unbalance should be different for each individual curve. To overcome the weaknesses of using a blanket unbalance superelevation and to gain higher speed, a new formula is suggested.
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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 | 0.001 |
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; 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".