Nutrient-chlorophyll relationships: an evaluation of empirical nutrient-chlorophyll models using Florida and north-temperate lake data
Bibliographic record
Abstract
Nutrient-chlorophyll (CHL) relationships were developed using a large data set collected in Florida over the last 10 years consisting of monthly total phosphorus (TP), total nitrogen (TN), and CHL concentrations from 360 lakes. The precision of these and five additional published relationships was examined. The 95% confidence interval for the best available TP-CHL model is 30-325% of the calculated CHL value. Analysis of associated Florida monthly nutrient and CHL data indicate that the TP-CHL relationship is sigmoid, although a linear response is found for TP concentrations in the range of 3-160 µg·L -1 . The maximum CHL responses for a sigmoid curve and straight line are similar for TP concentrations of 3-100 µg·L -1 . Both relationships describe P limitation when the CHL response falls on or near the line and provide a benchmark to evaluate other limiting or colimiting factors that are indicated when the CHL response falls below the line. Florida and global data are similar, exhibiting a lessening of slope above a TP concentration of 100 µg·L -1 . A global median line is derived from a large population of lake data for use in general lake management.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".