Potential Arctic connections to eastern North American cold winters
Bibliographic record
Abstract
Far-field temperature and geopotential height fields associated with eastern North American early winter (DEC-JAN) extreme cold events are documented since 1950. Based on 19 cases of monthly extreme cold events, two large-scale patterns emerge. First, a strong Alaskan Ridge (AR) can develop with higher 700 hPa geopotential heights and positive temperature anomalies from Alaska south along the coastal northeastern Pacific Ocean, and low eastern North American geopotential height anomalies, the well-known North American ridge/trough pattern. A second subset of cases is a Greenland-Baffin Blocking (GBB) pattern that have positive temperature anomalies centered west of Greenland with a cut off tropospheric polar vortex feature over eastern North America; cold temperature anomalies extend from southeastern United States northwestward into central Canada. Both of these historical large-scale patterns associated with eastern North American cold events (AR and GBB) have the potential for future reinforcement by sea ice loss and associated warm Arctic regional temperature anomalies. An example of a GBB case is 15-22 December 2010 and an extreme AR case is in early 4-14 December 2016. In both cases lack of sea ice and warm temperature anomalies were colocated with local maximums in the geopotential height anomaly fields. Future regional delay of fall freeze up in the Chukchi Sea and Baffin Bay regions could reinforce these geopotential height patterns once they occur, but is not likely to initiate AR and GBB type events.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".