Evaluation of a combination of phosphorylated fibers and zeolite as a potential substitute to synthetic wetting agents in peat moss products
Bibliographic record
Abstract
Water availability and pH are important factors to consider to determine the suitability of a material for use as a growing medium. Unfortunately, most horticultural substrates are characterized by their water repellency. This is the case with peat moss which is hydrophobic and acidic. Synthetic surfactants are required to improve its wettability. In this study, a combination of phosphorylated wood pulp fibers (FLP) and zeolite is proposed as a substitute to surfactants to increase the wettability of peat moss in the presence of lime, an additive generally used as fertilizer or pH regulator. Results show that lime reduces the water retention capacity of FLP. However, the addition of 15% zeolite to the peat moss/FLP system increases the pH and water retention of the substrate. The negative effect of the presence of 1 wt. % lime on the water retention of the peat moss/FLP mixture was corrected by zeolite addition. Optimal conditions were obtained at 10% zeolite for the two types of lime tested with favorable pH and water retention capacity values. Zeolite was shown to have a higher affinity than FLP for calcium ions preventing the detrimental interaction between FLP and calcium ions.
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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".