Predicting environmental soil phosphorus limits for dissolved reactive phosphorus loss
Bibliographic record
Abstract
Abstract The dependence of runoff dissolved reactive phosphorus ( DRP ) loss on soil test P or rapid estimations of degree of P saturation ( DPS ) often varies with soil types. It is not clear whether the soil‐specific nature of runoff DRP versus DPS is due to the different sorption characteristics of individual soils or the inability of these rapid DPS estimates to accurately reflect the actual soil P saturation status. This study aimed to assess environmental measures of soil P that could serve as reliable predictors of runoff DRP concentration by using soils collected from Ontario, Canada, that cover a range of chemical and physical properties. A P sorption study was conducted using the Langmuir equation to describe amount of P sorbed or desorbed by the soil ( Q s , mg/kg) versus equilibrium P concentration ( C , mg/L) in solution, where Q max is P sorption maximum (mg/kg), k represents P sorption strength (L/mg), and Q 0 (mg/kg) is the P sorbed to soil prior to analysis. Runoff DRP concentration increased linearly with increasing DPS sorp (i.e. the ratio of ( Q 0 + Q D )/ Q max ) following a common slope value amongst soil types, while the P buffering capacity ( PBC 0 ) at C = C 0 yielded a common change point, below which runoff DRP concentration decreased greatly with increasing PBC 0 compared to that above the change point, where C 0 and Q D represent the equilibrium P concentration and amount of P desorbed, respectively. Both DPS sorp and PBC 0 showed great promises as indicators of runoff DRP concentration.
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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) | 0.000 | 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".