Investigation of average optical density and degree of liquids saturation in sand by image analysis method
Bibliographic record
Abstract
This research aims to apply an image analysis technique to investigate relationships between liquid saturations and Average Optical Densities (AODs) of four different porous media (i.e., Ottawa#3820, Ottawa#3821, Toyoura, and Chonburi sands). Water and diesel are used as liquids. Twenty tested samples, including 10 samples of air-water two-phase system and 10 samples of air-diesel two-phase system with variations of diesel and water saturations, are prepared for each porous medium. All samples are compacted into cylindrical containers then photos of each sample are taken by two digital cameras fitted with different band-pass filters. The photos are analyzed by an in-house program to obtain average optical densities for each spectral band. Relationships between AODs and liquid saturations are analyzed for each porous media. The results indicate that AODs are linearly proportion to degree of water and diesel saturations for all porous media in both spectral bands except Chonburi sand. The reason is due to the fact that Chonburi sand has a very rough surface which can absorb water and other liquids more than other media.
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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 | 0.003 | 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".