Variability in the climate of the Pacific Ocean and North America as expressed in the Mount Logan ice core
Bibliographic record
Abstract
Abstract In this paper, we explore the climate signal contained in the annual snow-accumulation time series from a high-altitude ice core drilled on Mount Logan in the Saint Elias mountain range of western Canada. With the global meteorological fields from the U.S. National Centers for Environmental Prediction re-analysis, we construct composites of the atmospheric circulation and temperature patterns associated with anomalous snow accumulation at the Mount Logan site over the period 1948–87. These results confirm, with an independent method, previous work that identified the existence of a coherent upper-tropospheric circulation anomaly extending over much of the North Pacific Ocean and North America that is associated with snow accumulation at the site. This anomaly has a similar structure to that associated with the extratropical response to the El Niño–Southern Oscillation. Coherent structures consistent with this circulation pattern also exist in both air- and land-temperature fields. In particular, heavy (light) snow accumulation at the site is associated with warmer (colder) air and surface temperatures over the North Pacific Ocean and North America. Over the North Pacific, the sea-surface temperature anomaly associated with heavy snow accumulation at the site has a “horseshoe” pattern that is similar to that associated with the Pacific Decadal Oscillation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".