Comparing past and present climate – a tool to distinguish between natural and human-induced climate change
Bibliographic record
Abstract
Variations in climate over the last approx. 2000 years and a contrast in the winter climate regime of NW Europe and West Greenland may be ascribed to variations in the teleconnection pattern expressed by the North Atlantic Oscillation (NAO). This well-known climate phenomenon is, among others, reflected in an increased inflow of warm Atlantic Water into the Labrador Sea under conditions of a colder European winter regime (negative NAO indices). Cooling of the Labrador Sea appears to have been a feature typical for a milder European winter climate (positive NAO indices). This pattern is seen both on shorter, (sub)decadal timescales of the last approx. 60 years and on a longer, centennial timescale through the last millennia. During a significant part of the 20th century warming, episodes of milder winters in Europe may be related to Atlantic patterns of natural climate variability similarly as recorded in the past millennia. However, records for recent decades (since the mid 1980s) show a different pattern indicating a significant change in North Atlantic ocean- and atmospheric circulations. This seemingly changed behaviour of the climate system corresponds in timing to the episode of the most extensive global temperature increase, suggesting an increasing anthropogenic effect on the climate development of the past ca. 20 years.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".