Modulus Mapping of MnROAD Pavement Foundation Layers
Bibliographic record
Abstract
Several test sections at the MnROAD pavement research facility in Minnesota were re-constructed in summer 2022. Roller modulus mapping was performed to assess foundation layer support conditions, with independent calibration using in situ cyclic plate load tests, and the results are compared with the assumed design values. A new approach was implemented to develop field target values that linked the design loading case with the in situ cyclic plate load testing considering geomaterial stress-dependency, realistic stress-state conditions, and the measurement influence depth of the loading plate. e-Compaction reports were generated for the modulus mapping runs in near real-time to proactively address poor support conditions. Spatial maps of resilient modulus and “blob” analysis maps showing contiguous poor support were generated to improve performance ranking of current experiments. The mapping results identified low modulus areas and allowed for analysis of variability, differences in support conditions between the sections, and between passing and driving lanes.
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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 | 0.000 |
| 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) | 0.001 | 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".