Sulfur-enriched biochar as a potential soil amendment and fertiliser
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hydrogen sulfide (H2S) is a highly toxic and corrosive contaminant gas co-generated during anaerobic digestion. Studies have shown that biochars have the potential to adsorb H2S and to promote its oxidisation. To date, no studies have investigated the bioavailabilty to plants of the sulfur (S) contained in biochar when used as an S fertiliser. Biochar was packed into the biogas emissions stream to adsorb the H2S being generated. The resulting sulfur-enriched biochar (SulfaChar) and synthetic S fertiliser (control treatment) were amended to potting soils and the growth response of corn (Zea mays L.) and soybeans [Glycine max (L.) Merr.] and nutrient uptake were measured after a 90-day greenhouse study. SulfaChar contained 36.5% S (S element and SO42–), confirming it adsorbed significant amounts of H2S. Compared with the control treatment, SulfaChar amendment significantly increased corn plant biomass, ranging from 31% to 49% but only a slight increase in soybean biomass (4 to 14%). SulfaChar also increased corn plant uptake of S and other macro- (N, P, K, Ca, and Mg) and micro-nutrients (Zn, Mn and B). Our results show that SulfaChar was a source of plant available S, suggesting that SulfaChar is either a supplier of these nutrients or that it promoted their uptake.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
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 it