Modeling the effect of development on internal phosphorus load in nutrient‐poor lakes
Bibliographic record
Abstract
A steady state lake phosphorus (P) mass balance model was used to predict the equilibrium P concentration (annual, volume‐weighted average) of the lake water from natural and anthropogenic, external and internal P inputs. Internal P load was modeled as the product of sediment release rates and anoxic factors. Both these components were predicted from lake P concentration computed from external load to create a link between external and internal load components. Such estimates allow the modeling and setting of objectives of several hundred lakes on the Canadian Shield. In particular, estimates of predevelopment lake P concentration made by removing all anthropogenic inputs were compared with postdevelopment conditions in which additional loading was added to the model. This was accomplished by determining how much development would increase external as well as internal phosphorus load and ultimately annual average lake P concentrations. By comparing proposed lake development scenarios with existing or predevelopment scenarios, it can be determined whether water quality objectives will be exceeded.
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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 | 0.002 | 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 | 0.000 |
| 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".