PREDICTION OF LIFESPAN OF RAILWAY BALLAST AGGREGATE ACCORDING TO MECHANICAL PROPERTIES OF IT
Bibliographic record
Abstract
As the railway lifespan is the main criterion for selection of the aggregate for ballast and for planning the maintenance of the railroad, it is important to define the relationship between the particle load resistant characteristics and a lifetime of ballast in structure. Assessment of the quality of the ballast aggregate particles under dynamic and static loading reflect both, the toughness and hardness, and these are identified with the Los Angeles Abrasion and Micro-Deval Abrasion values. The model formerly developed by Canadian Pacific Railroads was adapted to predict possible loads expressed in cumulated tonnes. Different ballast aggregate mixtures were tested in the laboratory including dolomite and granite. Calculated potential gross tonnage (expressed in Million Gross Tonnes) of the railway per lifetime for each different aggregate type presented. The outcome of this research is established classification system of railway ballast aggregate and defined Los Angeles Abrasion and Micro-Deval Abrasion values of aggregate dependently on required lifetime.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".