Phosphorus and chlorophyll in the Bay of Quinte: A time-series/intervention analysis of 1972–2008 data
Bibliographic record
Abstract
Three independent methods of time-series analysis were applied to a 37-year record of total phosphorus and chlorophyll-a data collected at four sampling stations representing the upper, middle and lower sections of the Bay of Quinte, NE Lake Ontario, Canada. The three methods were used to build consensus around the significance of the apparent declines in total phosphorus (TP) and chlorophyll-a (Chl-a) concentrations following two interventions: (1) point-source phosphorus loading reductions of about 50% to the upper bay in the winter of 1977–1978 and (2) the establishment of Zebra Mussels (Dreissena spp.) in the early to mid-1990's. The methods were applied to May to October monthly means and included: (1) nonparametric tests that accounted for persistence and seasonality and determined the statistical significance of step-trends, (2) ARIMA-Intervention modelling that produced forecasts into post-intervention time periods that were compared statistically to measured data and (3) regime shift detection for identifying the significance of persistent steps after removal of the seasonal components of the data series (modelled as periodic functions). Strong gradients in total phosphorus (TP) and Chl-a concentrations between the upper and lower Bay of Quinte still existed three decades after reductions in point-source loadings of TP to the upper bay, where, during 2000–2008, May-October average TP was 3.8 times higher and Chl-a, 2.9 times higher than in the lower bay. The Remedial Action Plan May-October TP objective of 0.030 mg l-1 for the upper Bay of Quinte was not achieved consistently in recent years. Concurrence among the data analysis methods suggests that the relative decreases in the upper bay TP (31%) and Chl-a (37%) after phosphorus loading reductions were greater than in the lower bay (0% and 10%, respectively). The relative decreases in the upper bay TP (0%) and Chl-a (29%) associated with Dreissena establishment were less than those measured in the lower bay (20% and 50%, respectively).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".