Projected Climate Change and Variability and Their Impact on the Canadian Rocky Mountains
Bibliographic record
Abstract
Climate has changed in the historical past, sometimes very dramatically (like the Little Ice Age), and will continue to change in the future. However, since the onset of the Industrial Revolution in the mid-1800s, we have been conducting (unwittingly or not) a global geophysical experiment by emitting into the atmosphere an exponentially increasing amount of greenhouse gases, mainly carbon dioxide (CO2) originating from fossil fuel combustion (coal, oil, natural gas, etc.), short circuiting the natural global carbon cycle. Another major anthropogenic source of CO2 is the deforestation activities, mainly in the tropical regions. Based on the basic understanding of the radiative physics, the addition of these greenhouse gases has resulted in an overall increase in the global surface temperature, amplifi ed by an increase in atmospheric water vapour through positive hydrological feedback. “There is unequivocal evidence that Earth’s lower atmosphere, ocean, and land surface are warming; sea level is rising; and snow cover, mountain glaciers, and Arctic sea ice are shrinking. The dominant cause of the warming since the 1950s is human activities.” (AMS Statement on Climate Change 2012).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".