Physical circulation in the coastal zone of a large lake controls the benthic biological distribution.
Bibliographic record
Abstract
There are gradients of conductivity and major ions in the coastal zone of the Eastern Georgian Bay of Lake Huron that appear to limit the spatial distribution of invasive dreissenid mussels. Rivers flowing into Georgian Bay from the Canadian Shield are relatively low in conductivity compared to the main body of Lake Huron, and so there is an observed gradient of solutes near the river mouths. The field observations show a strong positive correlation between conductivity and calcium concentration. Thus, we use conductivity to infer the solute concentrations required for the successful growth of dreissenid mussels. We observe most mussels in regions where specific conductivities were greater than 140 mS/cm. We use field observations to examine how the low calcium river water mixes within the coastal zone, which sets solute gradients that determine mussel distribution. When river flows are low, there is only a weak solute gradient across the coastal zone, implying an intrusion of open bay waters into the shallow embayments that is favourable for the growth of mussels. In contrast, when river flows are as much as 10 times higher, there is a strong solute gradient that extends further towards the lake, and the low calcium appears to inhibit and limit the growth of dreissenid mussels. Thus, the seasonal character of solute gradients helps describe the spatial distribution of dreissenid mussels and helps explain the localized absence of a species that is otherwise prevalent in much of the Laurentian Great Lakes.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".