Synergistic application of modified zeolite and biochar in improving the performance of sandy vegetation concrete
Bibliographic record
Abstract
The combined use of zeolite (ZL) and biochar (BC) can effectively address the problems of poor anti-erodibility and fertility retention capacity of vegetation concrete (VC) prepared from sandy soil. Natural ZL (NZL), especially clinoptilolite, has some disadvantages, such as presence of numerous impurities distributed in the pores and low surface activity, which lead to insufficient adsorption ability. To fully utilize the synergistic effect of ZL and BC, NZL was modified into physical (PZL), chemical (CZL), and composite-modified ZL (SZL). Results showed trend in the average pore size was SZL > CZL > PZL > natural ZL, and the changes in the functional groups on the surface of SZL was the most significant. Modified ZLs enhanced VC performance: PZL had the strongest effect on anti-erodibility, while SZL was most effective in improving fertility and retention. Our results provided a useful method for treating engineering defects in VC prepared using sandy soil.
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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) | 0.000 | 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".