Bibliographic record
Abstract
The aim of this paper is to show to what extent natural conditions and environment are a factor in the distribution of population in Canada and their division into north and south. How it historically affected the different cultural and economic development of Canada, the deep regionalism between the North and the South. How much that modern climate change has an affect on ?opening? the region of North Canada (the territories of Nunavut, Yukon and Northwest territories). By analyzing climate tables and maps and comparing them, we conclude about the magnitude of climate changes that have occurred in that region in the last few years and decades and their positive and negative effects on the local population. The results showed that this historical "barrier" of the region is slowly "melting" with the ice. This paper is significant for two reasons, the first is to explain the historical division of the country through natural conditions as the main factors of division (into the southern more populated part and the northern sparsely populated part of Canada) and second to show how climate change really changes the everyday life of the local population in a positive (economic growth and employment) and negative (environmental change due to climate change and environmental pollution due to the arrival of industry in those "remote" areas) aspect.
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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 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".