Analysis of volumetric properties of bituminous mixtures using cellular phones and image processing techniques
Bibliographic record
Abstract
This study aims to develop the microanalysis of the bituminous mixtures using cellular phone images (CPI) and image processing techniques (IPT). A new methodology and scheme was developed for faster and accurate procedure to compute volumetric design parameters; voids in mineral aggregate (VMA), voids in total mix (VTM), and voids filled with asphalt (VFA) using CPI and IPT instead of the conventional methods. Five types of cellular phones with different camera resolutions were used to analyze the horizontal cross section (face) of hot mix asphalt slices. A cellular phone digital mapping frame for microstructure of the bituminous mixture for data collection was designed and implemented. New models for computations of volumetric design perimeters (VMA, VTM, and VFA) were developed. Results showed that the best cellular phone for microanalysis of the bituminous mixture is type D, even though it does not have the highest resolution, and the best height of capturing the images is 35 cm.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".