Application of molecular technologies to monitor the microbial content of biosolids and composted biosolids
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
Disposal of human biosolids is a source of concern for public health and the environment. Composting appears to be an interesting alternative to traditional disposal methods as it can decrease the load of human pathogenic microorganisms often present in biosolids and yield an end-product rich in nutrients for use as a soil supplement. Assessing the exact microbial content of biosolids, both for biosafety and operational reasons, has traditionally relied on the use of standard microbiological methods. Recent developments in molecular-based technologies now offer more rapid and specific monitoring of microorganisms in biosolids than culture-based methods. In this study, denaturing gradient gel electrophoresis (DGGE) was adapted to monitor the succession of bacteria in composted biosolids through different steps of compost production. Secondly, a TaqMan quantitative real time PCR (qPCR) approach was developed to detect and quantify the presence of Salmonella species, a model human pathogenic bacterium, susceptible to be found in biosolids. DGGE results indicated that the bacterial content of composted biosolids of different ages belongs to various taxa and significantly changes with age. qPCR results indicated that the quantity of Salmonella species found in composted biosolids ranging from 1 to 24 months significantly decreases with composting time.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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