Phosphorus and nitrogen loading depths in fluvial sediments following manure spill simulations
Bibliographic record
Abstract
Armstrong, S. D., Smith, D. R., Owens, P. R., Joern, B. C., Leytem, A. B., Huang, C.H. and Adeola, L. 2011. Phosphorus and nitrogen loading depth in fluvial sediments following manure spill simulations. Can. J. Soil Sci. 91: 427–436. The depth of nitrogen (N) and phosphorus (P) loading in fluvial sediments following a manure spill has not been documented. Thus, the objectives of this study were: (i) to determine the depth of N and P enrichment as a result of a manure spill under base flow conditions using fluvarium techniques and (ii) to evaluate the impact of sediment particle size distribution on N and P enrichment depth. Manure spills were simulated using stream simulators and ditch sediments collected from agricultural drainage ditches. During the manure spill simulation, the P sorption capacity of all sediments exponentially decreased with time and the NH4-N sorption capacity remained constant with time. The P and NH4-N loading in all sediments were observed to the depth of 2 cm, but were most concentrated in the 0- to 1-cm depth ranging in concentrations from 3 to 12 mg P kg−1 and from 7.2 to 45 mg NH4-N kg−1. Data from this study give a basis for the advancement of manure spill remediation that will reduce the impairment of surface waters via the release of nutrients from enriched sediments following a manure spill.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".