Seasonal Quantification of Coastal Processes and Cliff Erosion on Fine Sediment Shorelines in a Cold Temperate Climate, North Shore of the St. Lawrence Maritime Estuary, Québec
Bibliographic record
Abstract
A quantification of coastal erosion processes on a clay cliff in a cold temperate region was conducted. This study was based on a network of markers that were measured on a monthly basis from 1998 to 2003. During that period, the average retreat rate of the cliff was 1.5 m/y. Our results demonstrate that weathering is a more significant cliff retreat factor than hydrodynamic processes on fine sediment shorelines. This statement opposes conventional understanding. In fact, 65% of the annual cliff retreat took place through the winter season when the waves could not reach the foot of the cliff because of an ice foot. This erosion is caused by cryogenic processes in winter, particularly through freeze–thaw cycles, whereas desiccation and wave undercutting contributed respectively for 20% and 15% of the total annual retreat. The field measurements conducted before and after major storms, especially on October 29, 2000, illustrated that wave undercutting was negligible for the clay cliff. These results do not corroborate with previous studies showing that cliff erosion is mostly controlled by wave undercutting with negligible winter erosion. In a context of global warming, the intensity of cryogenic processes can become more important due to milder winters, an increase in the number of freeze–thaw cycles, and the reduction of the ice foot and snow cover (especially on south-facing cliffs directly exposed to solar radiation). This study demonstrates that the evaluation of sensitivity of coastal systems to climatic change should not be done just for sea-level rise and increased storminess, but also for other climatic parameters. Future research should also take into account approaches combining the studies of marine and terrestrial erosion processes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".