Tackiness of a novel biodegradable binder for erosion control mulch
Bibliographic record
Abstract
Kraft lignin, acidic (LA) and alkaline (LB) types, byproducts of pulp manufacturing were mixed with crude glycerol, a by-product of biodiesel production, and humic acid to produce a mulch tackifier for soil erosion control. Lignin was dried at 70°C for 24 h before use. The study was a full factorial with lignin levels of 20, 50, and 80% and humic acid levels of 1, 2, and 5% (w/w). The remaining portion consisted of crude glycerol. The samples were homogenized using water to facilitate the homogenization process. After homogenization, the samples were left to settle for 36 h and then separated into solid and liquid portions. Both portions were dried at 70°C for 24 h and tested for tack after wetting with water. Dried lignin, as a standalone ingredient, was also tested for tack. The values for the strength of tack were compared to those obtained from a commercial tackifier. Acidic lignin could be used with lignin content ≥50%. Acidic lignin was comparable to the commercial tackifier, whereas alkaline lignin was found to have significantly more tack but was found to be unsuitable for soil erosion use.
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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".