A Simple Field Method to Qualify the State of Saturation in Capillary Barriers
Bibliographic record
Abstract
Abstract A simple and straightforward field method to rapidly qualify the state of saturation of moisture retaining layers (MRL) is proposed and the details of its calibration and operation, described. The technique is based on the simple fact that if gas samples cannot be taken from a stainless tube that is inserted to the desired depth within the MRL, the air filled voids at that depth are not interconnected and the material can be qualified, for all practical purposes, as saturated. In this case, the threshold degree of saturation beyond which gas flux substantially decreases (approximately 85%), has been attained. In several sites covered with deinking by-products (DBP), an industrial residue that can be used as alternative construction material for landfills and acid-producing mine sites covers, it has been often impossible to collect gas samples below approximately 20 cm from the surface of the DBP layer. The question was thus to know if this is a reliable indicator that the threshold degree of saturation has or not been attained and that the layer is performing its role of gas barrier. In order to answer this question, a calibration was performed in the laboratory and in the field. The calibration consisted mainly on attempting to extract gas from samples compacted at different degrees of saturation. The results show that the threshold degree of saturation for DBP is attained at approximately 83%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".