Climate Change & Cold Weather Extremes an Overlooked Issue in The Present Climate Debate
Bibliographic record
Abstract
The debate on warming of the earth's climate due to rising levels of atmospheric CO 2 and associated climate change has gone on for over 40 years.Environmentalists and news media continue to point out increasing incidences of extreme weather events (e.g., heat waves, droughts/floods) and their harmful impacts on human societies.There is mounting evidence of increase in cold weather extremes which is at odds with the pervasive view of a warming climate.This paper deals with this overlooked but important issue of climate change and cold weather extremes.A brief overview of the global warming science as espoused by the UN climate body; IPCC (Intergovernmental Panel on Climate Change) is presented.Several examples of cold extremes since the new millennium are provided and briefly discussed.Short comments on the perceived "Climate Catastrophe" and the 'net-zero-by-2050' theme are provided in the end.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".