International Year of Planet Earth 7. Oceans: Submarine Landslides and Consequent Tsunamis in Canada
Bibliographic record
Abstract
Canada has the longest coastline and largest continental margin of any nation in the World. As a result, it is more likely than other nations to experience marine geohazards such as submarine landslides and consequent tsunamis. Coastal landslides represent a specific threat because of their possible proximity to societal infrastructure and high tsunami potential; they occur without warning and with little time lag between failure and tsunami impact. Continental margin landslides are common in the geologic record but rare on human timescales. Some ancient submarine landslides are massive but more recent events indicate that even relatively small slides on continental margins can generate devastating tsunamis. Tsunami impact can occur hundreds of km away from the source event, and with less than 2 hours warning. Identification of high-potential submarine landslide regions, combined with an understanding of landslide and tsunami processes and sophisticated tsunami propagation models, are required to identify areas at high risk of impact. SOMMAIRE Le Canada possede les plus longues zones cotieres et marges continentales du monde. Donc, il est significativement expose aux georisques marins, comme les glissements de terrain sousmarins (GTSM) comportent egalement des risques de tsunamis. Les glissements cotiers representent un risque significatif vu la proximite d’infrastructures et leur capacite de produire des tsunamis. Ils se produisent sans aver-tissement et peu de delai existe entre leur declenchement et l’impact possible d’un tsunami. Les GTSM en marge continentale sont communs dans l’histoire geologique mais rare a l’echelle de l’histoire humaine. Quelques anciens depots glisses sont de dimensions importantes, mais les nouvelles evidences suggerent que meme les petits glissements sur les marges continentales peuvent generer des tsunamis. L’impact des tsunamis peut etre ressenti a des centaines de km de la source et l’impact est possible avec moins de 2 heures d’avertissement. L’identification des regions a potentiel eleve pour l’instabilite des pentes combinees a la comprehension des processus de formation de GTSM et de tsunami, et a des modeles sophistiques de propagation, sont necessaires pour identifier les secteurs hautement a risque d’impact.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.039 |
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".