On the compressibility of tire-derived aggregate: comparison of results from laboratory and field tests
Bibliographic record
Abstract
Compression behavior of tire-derived aggregate (TDA) was investigated through relatively small-scale and large-scale laboratory one-dimensional compression tests, as well as a full-scale field test. Two types of TDA produced from passenger and light truck tire (PLTT) and off-the-road (OTR) tire were tested. The influence of initial void ratio (e0), particle size, tire source, and testing method on the compression behavior of TDA was investigated. The results indicated that the compressibility of TDA was primarily dominated by its e0. OTR yielded lower e0 than PLTT with similar particle size and the same compaction method. TDA in the field was pre-compressed by self-weight, resulting in lower e0 and compressibility compared with laboratory samples. At relatively high stress levels, all TDA exhibited similar void ratio–stress curves regardless of e0, particle size, tire source or testing method. High e0, small particle size, and granular particle shape facilitated the sliding and rolling of TDA particles, resulting in high plastic strain. The elastic deformation of TDA, reflecting the elastic behavior of tire rubber, was primarily dominated by the average contact area ratio of the TDA particles, depending mainly on the sample void ratio.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".