Network-level evaluation method of the overall–intralayer–interlayer interface structural states of semi-rigid asphalt pavement
Bibliographic record
Abstract
The pavement structure strength index (PSSI) indicator in the Chinese standard and the structural number (SN) indicator proposed by AASHTO are widely used to evaluate the structural states of semi-rigid asphalt pavement. However, PSSI and SN indicators do not involve the intra- and interlayer interface structural state, and the indicators are disconnected from the pavement design indicators. In this study, the intralayer remaining life and structural attenuation state were considered comprehensively to propose the indicators of the surface/base/subgrade structural state index (SSSI/BSSI/GSSI). The interlayer interface structural state index (ISSI) was proposed based on the friction coefficient between the surface and base layers. The pavement structural state index (PaSSI) was proposed by assigning the weightings to SSSI, BSSI, GSSI, and ISSI indicators. Compared with the PSSI or SN indicators, the proposed indicators realize the intralayer–interlayer–overall structural evaluation of the pavement, and the indicators were based on the pavement design indicators.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".