Assessing and predicting phosphorus phytoavailability from sludge incineration ashes
Bibliographic record
Abstract
Incineration of municipal sludge and agri-food by-products generates large quantities of ash that can be used in agriculture as phosphorus fertilizer. The fertilizing potential of sludge incineration ash (SIA) from 12 cities in Canada and the United States was tested in a greenhouse experiment against a synthetic fertilizer (TSP: triple superphosphate), a natural fertilizer (RP: rock phosphate), and a control without any P fertilizer. Two soil types were used: clay and sandy loam. A reliable a priori indicator of SIA P bioavailability was determined using the random forest method. SIA application increased ryegrass P uptake. The SIA relative P effectiveness (RPE), compared to the TSP, varied from 5.1% to 46.2% depending on the sludge origin and P solubility. SIA RPE was greater than RP for the clay soil but similar for the sandy loam soil. The neutral ammonium citrate (NAC) extraction, sometimes inappropriately used to characterize P availability of sludge and by-products, explained only 53% of the RPE variation. The random forest analysis showed that the oxalate extraction (Al, P, and Fe) is a better indicator (R2 = 0.94) of relative availability of SIA than the NAC P solubility (R2 = 0.86), and that Al content is the factor that influences most SIA P solubility. Based on our findings, we recommend the use of the Al, Fe, and P oxalate extraction to predict the SIA P availability, instead of the widely used NAC method which extracts only P.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".