Development of Failure Scenarios for Biosolids Land Application Risk Assessment
Bibliographic record
Abstract
Although deviations from standard guidance for land application of biosolids occur in practice, their importance is largely unknown. A list of such deviations (plausible failure scenarios) were identified at a workshop of industry, regulators, and academic professionals. Next, a survey of similar professionals was conducted to rank the plausible failure scenarios according to their severity, frequency, incentive to ignore control measures, gaps in existing control processes, public concern, and overall concern. Survey participants rated intentional dumping (unpermitted disposal) as the most severe of the failure scenarios, lack of worker protection as the most frequent scenario, and application of Class A biosolids that have failed to meet treatment standards as the scenario for which incentives to ignore control measures are highest. Failure of public access restrictions to application sites was the scenario for which existing controls were judged the weakest; application of biosolids too close to wells was ranked highest for public concern and for overall concern. Two scenarios for which existing controls were considered weaker, site restriction violations and animal contact leading to human exposure, were also rated as frequently occurring. Both scenarios are related in that they (1) involve inappropriate access to a site before the required time has elapsed, and (2) could be addressed through similar biosolids management measures.
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.
How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".