Transport of phosphorus and nitrogen in surface runoff in a corn silage system: Paired watershed methodology and calibration period results
Bibliographic record
Abstract
Jokela, W. E and Casler, M. D. 2011. Transport of phosphorus and nitrogen in surface runoff in a corn silage system: Paired watershed methodology and calibration period results. Can. J. Soil Sci. 91: 479–491. Transport of P, N, and sediment via runoff from crop fields, especially where manure has been applied, can contribute to eutrophication and degradation of surface waters. We established a paired-watershed field site to evaluate surface runoff losses of nutrients and sediment from different manure/crop/tillage management systems for silage corn production. During the 2-yr calibration period the four 1.6-ha watersheds, or fields, were treated identically with fall dairy manure application and chisel plowing, and runoff was monitored, sampled, and analyzed for suspended sediment (SS) and total and dissolved forms of P and N. That management was maintained as a control in one watershed, while alternative management systems were initiated on the three treatment fields. During the calibration period both concentrations and loads of SS and total and dissolved P and N varied by field and over 50% of runoff and dissolved P and N was from snowmelt runoff. Linear regressions of treatment fields against the control field were highly significant for runoff and concentrations and loads of all constituents. The estimated minimum detectable change (difference between means) was 10 to 30% for most parameters, suggesting a reasonable probability of success in detecting change in the treatment period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 |
| 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".