Modification of the Relation Between Grade and Curvature — Purpose, Reasons, and Advantages
Bibliographic record
Abstract
In cases where grades and horizontal curves are combined, the current relation between the grade and the degree of curve, D, is defined as follows:G+cD=r in which G = The maximum allowable compensated grade in %, D = Degree of curve, c = 0.04, compensation factor in % grade per degree of curve, r = The maximum grade achievable by the train in %. The above relation is a design tool to combine grade and curvature. The author intends to modify the above relation for two purposes — • to make the relation more rational for combining grade and curve for LRT design, and • to make the relation useful in computing the installation slope of special trackwork. A modified formula is suggested as under:G+cD=kr in which c = compensation factor in % grade per degree of curve determined on the basis of curvature, k = grade reduction factor arbitrarily chosen between 0.2 ∼ 1 depending on curvature and type of rail. The justification of the proposed modification and the advantages of the modified formula are discussed in details.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".