L'érosion hivernale de la falaise de Rivière-Saint-Jean, Québec : une comparaison entre les années de gel prolongé et des hivers doux
Bibliographic record
Abstract
RÉSUMÉ : Ce projet de recherche avait pour but d'étudier l'érosion de la falaise meuble à Rivière-Saint-Jean, sur la Côte-Nord, Québec, entre 2016 et 2021, en se concentrant particulièrement sur l'hiver sans glace côtière de 2020-2021. Le projet se concentre sur l'ampleur et les taux d'érosion qui ont été mesurés à partir de levés topographiques (LiDAR) qui ont été répétés à une fréquence mensuelle ou semestrielle. La dynamique côtière est décrite dans le contexte du régime thermique de la falaise basé sur des mesures in situ pendant l'hiver 2020-2021, et qui est étendu au reste de la période en utilisant un modèle empirique de la progression des fronts de gel et de dégel. Un contexte environnemental supplémentaire est donné par les tendances des tempêtes et des températures au cours de la période d'observation. Le taux moyen d'érosion entre novembre 2020 et avril 2021 a été de 8,1 m/an, ce qui est 2,5 fois plus rapide que la moyenne mesurée au cours de la période d'étude de cinq ans. Une combinaison de facteurs environnementaux tels que l'absence de glace côtière protégeant la falaise de l'action des vagues et les cycles fréquents de gel et de dégel déstabilisant la falaise de silt ont probablement contribué de manière importante à l'érosion rapide. -- Mot(s) clé(s) en français : géomorphologie côtière, érosion côtière, processus cryogéniques, gel-dégel, falaises meubles. -- \nABSTRACT : The goals of this research were to investigate erosion of unconsolidated coastal cliff at Rivière-Saint-Jean, North shore, Quebec, between 2016 and 2021, with particular focus on the coastal-ice-free winter which occurred in 2020-2021. The project focuses on the magnitude and rate of erosion which was measured from LiDAR-derived digital topographic models which were repeated at monthly to semiannual frequency. The coastal dynamic is described in the context of the thermal regime of the cliff based on in situ measurements during the winter of 2020-2021, and which is extended to the rest of the period using an empirical model of freezing- and thawing-front progression. Additional environmental context is given by storm and temperature trends during the observation period. The average rate of erosion between November 2020 and April 2021 was 8.1 m/a, which is 2.5 times faster than the average rate measured over the five year study period. A combination of environmental factors such as absense of coastal ice protecting the cliff from wave action and frequent freezing and thawing cycles destabilizing the silt cliff were likely important contributors to the rapid erosion. -- Mot(s) clé(s) en anglais : coastal geomorphology, coastal erosion, cyogenic processes, freeze-thaw, unconsolidated cliffs.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".