Feldspathic sandstone addition and its impact on hydraulic properties of sandy soil
Bibliographic record
Abstract
Feldspathic sandstone could be used as an effective conditioner to improve the physical quality of sandy soil, and increase the crop yield there. To determine the effects of feldspathic sandstone content on soil hydraulic properties in a sandy soil, the present study added 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% (no sandy soil) of feldspathic sandstone to sandy soil. Changes in hydraulic parameters were investigated and the results showed addition of feldspathic sandstone increased saturated water content by 37%–61% and field capacity by 29%–44%, and decreased saturated hydraulic conductivity from 10.19 to 0.58 cm h−1 of the sandy soil. Further data analysis demonstrated that with increasing content of feldspathic sandstone, the parameter n of soil water retention curve in Van Genuchten model dropped from 1.807 to 1.333. The same decreasing trend is detected in parameter a of infiltration rate (3.841–0.703) in Kostiakov formula (i = at−b) and parameter a1 of wetting front (6.901–1.174) in the empirical equation (X = a1tb1). In terms of hydraulic parameters, 40% feldspathic sandstone and 60% sandy soil, optimally matching indices of loess soil, were the best mixing ratio for sandy land restoration.
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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 | 0.000 |
| 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) | 0.001 | 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".