Composting organic residues: Trace metals and microbial pathogens
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
Industrialized societies are responsible for increasing environmental pollution by trace metals, and pathogenic micro-organisms associated with products and wastes of industrial processes and agricultural production, as well as household activities. The objective of this paper is to discuss the effect of composting on the behavior of trace metals and pathogenic micro-organisms, and to present the latest finding on sanitizing and stabilizing organic fractions and trace metals in composted biosolids. Evidence provided by long-term scientific studies in North America and Europe on toxic effects of trace metals on soil micro-organisms and on pathogenic micro-organisms suggests that revisions of the current guidelines on sludge applications on agricultural soils are needed to protect long-term soil fertility. In addition, the antagonism between harmful characteristics of biosolids and their usefulness for agriculture and land reclaiming purposes could be mitigated by using efficient composting treatments. The production and use of harmless organic wastes should be one of our highest priorities in order to protect our health and environment, and to hand over a sustainable agriculture to future generations. Key words: Composting, biosolids, pathogenic micro-organisms, trace metals, sanitization
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 | 0.000 | 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 | 0.002 |
| 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 it