Selection of a Water‐Extractable Phosphorus Test for Manures and Biosolids as an Indicator of Runoff Loss Potential
Bibliographic record
Abstract
The correlation of runoff phosphorus (P) with water-extractable phosphorus (WEP) in land-applied manures and biosolids has spurred wide use of WEP as a water quality indicator. Land managers, planners, and researchers need a common WEP protocol to consistently use WEP in nutrient management. Our objectives were to (i) identify a common WEP protocol with sufficient accuracy and precision to be adopted by commercial testing laboratories and (ii) confirm that the common protocol is a reliable index of runoff P. Ten laboratories across North America evaluated alternative protocols with an array of manure and biosolids samples. A single laboratory analyzed all samples and conducted a separate runoff study with the manures and biosolids. Extraction ratio (solution:solids) was the most important factor affecting WEP, with WEP increasing from 10:1 to 100:1 and increasing from 100:1 to 200:1. When WEP was measured by a single laboratory, correlations with runoff P from packed soil boxes amended with manure and biosolids ranged from 0.79 to 0.92 across all protocol combinations (extraction ratio, filtration method, and P determination method). Correlations with P in runoff were slightly lower but significant when WEP was measured by the 10 labs (r=0.56-0.86). Based on laboratory repeatability and water quality evaluation criteria, we recommend the following common protocol: 100:1 extraction ratio; 1-h shaking and centrifuge 10 min at 1500xg (filter with Whatman #1 paper if necessary); and determining P by inductively coupled plasma-atomic emission spectrometry or colorimetric methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".