Prediction of phosphorus concentration in tile-drainage water from the Montreal Lowlands soils
Bibliographic record
Abstract
Subsurface drainage systems can be a significant pathway for P transfer from some soils to surface waters. The objective of the study was to determine P concentration in tile-drainage water and its relationship to P status in surface soils (A horizons) from an intensively cultivated area in the Montreal Lowlands. The profiles of 43 soil units were characterized for their P contents and pedogenic properties. Tile-drainage water P concentrations were monitored over a 3-y r period on a weekly basis on 10 soil units, and four times during each growing season for the other 33 units. The soil units were grouped into lower and higher P sorbing soils using multiple discriminant equations developed in an earlier related study. The A horizons of the lower P sorbing soils had an elevated P saturation degree [mean Mehlich(III) P/Al = 17%] associated with total P concentrations in tile-drainage water consistently greater than the surface water quality standard of 0.03 mg total P L-1. Conversely, low P concentrations in tile-drainage waters (< 0.03 mg L-1) and a moderate mean Mehlich(III) P/Al ratio of 8% were observed in the higher P sorbing soil group. Total P concentrations in drainage systems were significantly related to soil P status in surface soils. Grouping soils according to their P sorption capacities increased the power of prediction based on only one soil variable. However, accurate predictions in terms of drain P concentration can hardly be obtained unless large dataset and other factors related to field management practices and hydrology of the sites are also considered. Therefore, a better alternative to predict the risk of P leaching is to work in terms of risk classes and rely on a multiple factor index. Key words: Tile-drainage water, phosphorus, P transfer, P loss, degree of soil P saturation, phosphorus index
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".