Deformational behavior of fouled railway ballast
Bibliographic record
Abstract
Plastic strain of railway ballast subjected to various fouling conditions was determined under simulated traffic loading through testing with large-scale cyclic triaxial equipment. Mechanisms by which fouling material affects the plastic strain of railway ballast were investigated. Fouling content (% by weight of particles <12 mm) increased the plastic strain of ballast by contaminating the contact points of ballast particles. Increasing moisture (>3%) resulted in larger accumulation of plastic strain in fouled ballast under traffic loading. Soil-suction tests showed that plastic strain of fouled ballast with suction >2000 kPa is similar to that of clean ballast, regardless of fouling and moisture content. For noncohesive fouling material (mineral and coal fouling), plastic strain is affected by fouling and moisture; therefore, a noncohesive fouling index (NFI) is proposed. In cohesive (clay) fouling, plastic strain is controlled by moisture and fouling content, as well as compositional characteristics of the cohesive fouling material, primarily represented by Atterberg limits and % mass <0.075 mm. A cohesive fouling index (CFI) is proposed to characterize the deformation of cohesive fouled ballast.
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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".