Production of biochar for treatment of retting effluents and utilization of spent biochar as potential germination medium for leafy greens
Bibliographic record
Abstract
Biochar has been found to be suitable for a wide array of applications. However, the repurpose of spent biochar has been far less explored. In this study, we utilized biochar as a pH treatment for wastewater effluent obtained from the pineapple fibre retting process and then used the spent biochar as a growth substrate media in place of commercially and non-reusable substrates, such as peat and rockwool. Biochar produced from wheat straw was used to treat the effluent which was then characterized for macro and micronutrient content. Treatment of effluent with biochar increased the micronutrients in the effluent, such as the iron content by 10-fold and the manganese content by 5-fold. The biochar treated wastewater effluent from the pineapple fibre retting was used as hydroponic medium to grow basil and arugula. The spent biochar was subsequently used as a growth substrate medium as a replacement for rockwool and peat. Initial tests showed successful germination for basil and arugula.
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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 | 0.001 |
| 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".