Source‐Separated Municipal Solid Waste Compost Application to Swiss Chard and Basil
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
A growth room experiment was conducted to evaluate the bioavailability of Cu, Mn, Zn, Ca, Fe, K, Mg, P, S, As, B, Cd, Co, Cr, Hg, Mo, Na, Ni, Pb, and Se from a sandy loam soil amended with source-separated municipal solid waste (SSMSW) compost. Basil (Ocimum basilicum L.) and Swiss chard (Beta vulgaris L.) were amended with 0, 20, 40, and 60% SSMSW compost to soil (by volume) mixture. Soils and compost were sequentially extracted to fractionate Cu, Pb, and Zn into exchangeable (EXCH), iron- and manganese-oxide-bound (FeMnOX), organic-matter (OM), and structurally bound (SB) forms. Overall, in both species, the proportion of Cu, Pb, and Zn levels in different fractions followed the sequence: SB > OM >> FeMnOX > EXCH for Cu; FeMnOX = SB > OM > EXCH for Pb; and FeMnOX > SB = EXCH >> OM for Zn. Application of SSMSW compost increased soil pH and electrical conductivity (EC), and increased the concentration of Cu, Pb, and Zn in all fractions, but not EXCH Pb. Basil yields were greatest in the 20% treatment, but Swiss chard yields were greater in all compost-amended soils relative to the unamended soil. Basil plants in 20 or 40% compost treatments reached flowering earlier than plants from other treatments. Additions of SSMSW compost to soil altered basil essential oil, but basil oil was free of metals. The results from this study suggest that mature SSMSW compost with concentrations of Cu, Pb, Mo, and Zn of 311, 223, 17, and 767 mg/kg, respectively, could be used as a soil conditioner without phytotoxic effects on agricultural crops and without increasing the normal range of Cu, Pb, and Zn in crop tissue. However, the long-term effect of the accumulation of heavy metals in soils needs to be carefully considered.
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