Development of an automated method for continuous detection and quantification of cliff erosion events
Bibliographic record
Abstract
Abstract Three intrusive systems of detection and quantification of coastal erosion events (using thermocouples and thermal pins) were developed and tested from 2005 to 2008 in different regions of the Gulf and maritime estuary of the St Lawrence (Quebec, Canada). The 3‐m‐long thermal pins inserted inside unconsolidated deposits allow the monitoring of erosion for a time period sometimes extending over several seasons. The thermocouple or thermocable method allows not only the instrumentation of unconsolidated deposits but also of rocky and cohesive substrate to a depth of 85 cm. An autonomous microclimatic station located near the experimental sites simultaneously samples temperature parameters, precipitation, snow cover, wind speed and direction as well as global radiation. The differential analysis of cliff thermal regime performed simultaneously with an analysis of air temperature makes it possible to determine the activation periods of coastal erosion processes. The results also make it possible to establish with precision the actual influence of rapid variations of certain climatic and microclimatic parameters (radiation, presence of snow cover, precipitation, etc.) on the physical state of surfaces and also on the activation of certain physical processes connected to coastal erosion events. The automated thermal erosion pin system (ATEPS) allows high temporal resolution (i.e. continuous) monitoring, enabling a real coupling of coastal erosion rates and climatic parameters. Preliminary results with the ATEPS system indicate that mild winter temperature and direct solar radiation are significant factors controlling cliff retreat rates. Moreover, the melting of segregation ice during the spring thaw contributed for more than 70% of cliff retreat against only 30% for frost shattering. Copyright © 2010 John Wiley & Sons, Ltd.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".