Models to predict total phosphorus concentrations in coastal embayments of eastern Georgian Bay, Lake Huron
Bibliographic record
Abstract
Several coastal embayments of eastern Georgian Bay show signs of water-quality impairment thought to be caused by human activities. Here, we evaluate the ability of the Lakeshore Capacity Model (LCM), developed for Precambrian Shield lakes, to assess the impact of cottage development on the trophic status of ten Georgian Bay embayments. The LCM could only be applied to eight embayments due to the large size and complexity of two watersheds and produced unacceptably high estimates of mean seasonal total phosphorus concentrations ([TP]; i.e., exceeded 20% of measured values for five of eight embayments); accuracy of [TP] estimates could not be improved by accounting for internal phosphorus loading. We developed an additional model, the Anthro-Geomorphic Model (AGM), which uses building density and basin morphometry as variables. Estimates of [TP] for the AGM were within 20% of measured values for all sites. Compared with other aquatic systems, coastal embayments of Georgian Bay have significantly higher chlorophyll a concentrations per unit [TP]; we suggest that the TP–chlorophyll relationship presented in this study be used to estimate productivity in these systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".