International Year of Planet Earth 8. Natural Hazards in Canada
Bibliographic record
Abstract
Canada, the second largest country in the world, is subject to every hazardous natural process on Earth − large earthquakes, tsunami, volcanic eruptions, landslides, snow avalanches, floods, hurricanes, tornados, severe storms, drought, and sea-level rise. Fortunately, much of the country is sparsely populated; hence risk from these hazardous processes is localized to small areas adjacent to the Canada−US border, where most Canadians live. The greatest risk comes from earthquakes and landslides on the populated south coast of British Columbia and parts of southern Ontario and Quebec; from floods in Vancouver, Calgary, Winnipeg, or Toronto; and from hurricanes in Halifax and St. John’s. In the long term, Canada’s coastlines are threatened by sea-level rise and Canada’s northern indigenous peoples are threatened by permafrost thaw caused by global warming. SOMMAIRE Deuxieme plus grand pays de la planete, le Canada est expose a chacun des risques naturels sur Terre – grands seismes, tsunamis, eruptions volcaniques, glissements de terrain, avalanches de neige, inondations, ouragans, tornades, fortes tempetes, secheresses, et hausse du niveau de la mer. Heureusement, le pays est peu peuple en grande partie, et donc, le risque associe a ces phenomenes naturels est restreint a des bandes etroites le long de la frontiere separant le Canada et les Etats-Unis, la ou la plupart des Canadiens vivent. Les risques les plus eleves proviennent des seismes et des glissements de terrain le long de la cote sud peuplee de la Colombie-Britannique et certaines portions du sud de l’Ontario et du Quebec; d’inondations dans les villes de Vancouver, Calgary, Winnipeg, et Toronto; et, d’ouragans a Halifax et a Saint-Jean. Au long terme, les cotes canadiennes sont exposees a la hausse du niveau de la mer, et les peuples autochtones du Nord canadien sont menaces par le degel du pergelisol decoulant du rechauffement climatique.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.252 | 0.106 |
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".