Atmospheric teleconnection between Japan and the Saint Elias Moutains, Yukon (scientific paper)
Bibliographic record
Abstract
Cross correlation between time series of (1) total precipitation for a combined four-station network in northern Japan and of (2) the net snow accumulation determined from an ice core obtained from Mount Logan (60.5°N, 5340m) situated in the Saint Elias Mountains, Yukon, reveals high, statistically significant, cross correlation coefficients of +0.38 for annual data increasing up to +0.71 for seven point smoothing of the two 89 year series. The distance between sites is about 7000km spanning the complete Pacific Ocean between latitudes of about 40°N and 60°N. A review of the extensive literature of oceanology and climatology for the North Pacific Ocean region indicates that a strong coupling exists between the ocean and the atmosphere especially up to and associated with the Polar Front Zone along which major cyclogenesis occurs during most months of the year. Cyclones track generally from west to east with a strong northerly component especially in the eastern (Gulf of Alaska) sector. Examination of these cyclones on GOES satellite images shows that weather systems can transport moisture from mid latitude ocean sources (<40°N) to high on Mount Logan over the top of the warm front zone and high above intervening coastal topography. Thus, the positive correlation between the two time series can be physically justified and qualifies the link as a genuine teleconnection.
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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 | 0.002 |
| 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) | 0.001 | 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".