J. Great Lakes Res. 25(4):799–813 Internat. Assoc. Great Lakes Res., 1999 Seasonal, Interannual, and Spatial Variability in the Concentrations of Total Suspended Solids in a Degraded Coastal Wetland of Lake Ontario
Bibliographic record
Abstract
ABSTRACT. A 4-year (1993 through 1996) monitoring program examined the distribution of total sus-pended solids (TSS) in Cootes Paradise Marsh, a shallow (mean depth of 70 cm), degraded, drowned-rivermouth marsh of Lake Ontario. Monthly meteorological and hydrographical data from 1986 through 1996 revealed a hydrologically dynamic system that exhibited large seasonal and interannual variation with respect to precipitation amount, discharge volume, and water levels; the prevailing winds were shown to be oriented along the length of the marsh. Interannual variation in TSS concentrations was inversely related to mean seasonal water levels that fluctuated 45 cm over the 11 years. In a stepwise regression analysis, planktonic chlorophyll-a concentration only explained 2 % of the variation in TSS, while inorganic and non-algal organic solids explained 70 % and 18%, respectively. Mean seasonal water turbidity increased significantly with mean seasonal wind speed at 17 sampling stations during 1993 and 1994. Runoff from a summer rainstorm more than doubled water turbidities at the mouth of all three creeks over the first 36 hours. In enclosure experiments, water turbidity increased proportionately with biomass of benthivorous fish (especially common carp, Cyprinus carpio). When wind and carp distur-bance were compared simultaneously in the field, wind speed accounted for 41 % of the variation in tur-bidity while presence of carp explained an additional 21%. The overall temporal and spatial distribution of TSS in the marsh reflected changes in water level, wind activities, onset of rain events, and fish distur-bance that acted in concert to keep Cootes Paradise Marsh extremely turbid throughout the summer.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.042 |
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".