Sediment dynamics in the fluvial lakes of the St. Lawrence River: accumulation rates and characterization of the mixed sediment layer
Bibliographic record
Abstract
Permanent sedimentation ( 210 Pb and 137 Cs), sediment mixed layer thicknesses, and mixing coefficients ( 7 Be) were measured in the St. Lawrence River in order to evaluate the importance of sediment retention in the particulate matter budget and to characterize the system's resilience to changing contaminant loads. Net sediment accumulation (1 to > 18 kg·m -2 ·year -1 ) is observed at most sites deeper than 4.5 m located outside the main channels. Annual sediment retention in the lakes ranges from 1.5% (Lake St. Pierre) to 17% (Lake St. Francis) of their total load of suspended solids. 7 Be profiles indicate that the average mixed layer thickness, mixed layer mass, and mixing coefficient are 3.3 ± 0.2 cm, 17.8 ± 1.7 kg·m -2 , and 14.9 ± 2.8 cm 2 ·year -1 , respectively. The average depth of the long-term (approximately 5 years) mixed layer determined from the 137 Cs : anthropogenic Pb ratio is 5.1 ± 0.4 cm, corresponding to 30.6 ± 4.6 kg·m -2 . Because the mixing coefficient in superficial sediments is relatively high, and because annual particulate matter loading to the river is comparable with its mixed sediment inventory, the system is expected to have a rather short memory of past conditions and to recover rapidly (2-5 years) following a decrease in contaminant loading.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".