The influence of particle size on sand-pack properties and drying profile.
Bibliographic record
Abstract
The problem of underground contamination including contamination of potable water aquifers is more serious now than ever. Stringent pollution control laws as well as concern for the environment has given birth to the technology for remediation of contaminated soil and groundwater. The Research conducted thus has proposed a way to contain the contamination from underground storage tanks from spreading and travelling downwards using the principles of desiccation in in-situ formations. The desiccant barrier proposed here is the circulating air barrier (CAB) which utilizes the injection of dry gas or air to create an ultra dry zone in situ. Thus the injected gas carries along with it the moisture from the isolated zone so that any contaminant travelling in the desiccant zone must replace the previously removed water before they can mitigate any further. In order to utilize the CAB technology as a containment, it is highly necessary to evaluate the soil characteristics, porosity, permeability, drying rate etc. of the formation. The work presented here mainly deals with these issues as regards with sand type Ottawa silica size: 16-20. A comparison with the previously published work about smaller grain size sands is also presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".