Erosion of undisturbed clay samples from the banks of the St. Lawrence River
Bibliographic record
Abstract
In some regions the clay banks of the St. Lawrence River along the Montréal to Lac St. Pierre reach have recession rates of up to 13 m/year. The banks are formed of structured marine clays of the Champlain Sea (Leda clay). In this laboratory study, undisturbed samples of this high-plasticity inorganic clay taken at Îles de Verchères were subjected to a unidirectional current and a constant wave climate to investigate the mechanisms of erosion and the factors influencing erosion rates. Initially, surface erosion resulted in the formation and enlargement of cracks and the smoothing of competent surfaces. The dominant erosion process was a mass erosion of the blocks of clay delineated by the cracks. Desiccation or weathering significantly increased erosion rates, as tension cracks formed due to drying, and upon rewetting, the formation of microfissures resulted in disintegration into small, easily erodable flakes. The estimated critical shear stress of the samples was 620 Pa. For the St. Lawrence River, these results suggest that waves are the dominant erosion mechanism, with shipping contributing significantly to the erosion of banks close to the navigation channel. Weathering caused by wetting and drying from changing water levels or wave runup greatly increases erosion rates.Key words: erosion, Leda clay, undisturbed clay, natural clay structure, St. Lawrence River, waves, weathering, desiccation, vegetation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".