Non-Contact Sensing System to Measure Specimen Volume During Shrinkage Test
Bibliographic record
Abstract
Abstract The shrinkage curve provides information of value for the interpretation of soil-water characteristic curve data. However, there is need for an accurate and precise volume measurement technique during the shrinkage test. This paper presented an inexpensive automated digital image processing technique, which allowed accurate and precise measurements of the soil specimen volume. The volume was computed by accurately measuring the radius and height over the entire lateral surface of specimen. The proposed volume measurement technique involved projecting a structured light laser on the soil specimen in order to provide the reference points for measurements. A 360° view of the specimen was then captured using a camera. High resolution images were then processed using functions developed within MATLAB. The computations also allowed the reconstruction of a 3D mesh model of the specimen. A validation test on a dummy object showed that the error in radius and height measurements at more than 75 % measurement points was less than ±0.05 and ±0.07 mm, respectively. A 99 % accuracy was achieved in the volume measurement of the soil specimen.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".