Lagged teleconnections between snow depth in northern Eurasia, rainfall in Southeast Asia and sea‐surface temperatures over the tropical Pacific Ocean
Bibliographic record
Abstract
Abstract This study shows that above‐(below‐)normal winter snow depth over European Russia and corresponding below‐(above‐)normal snow depth over central Siberia is associated with reduced (increased) summer monsoon rainfall over southern and western India and eastern Pakistan, and above‐(below‐)normal sea‐surface temperatures (SSTs) over the eastern and central tropical Pacific Ocean during the following winters. The connection is slightly stronger when snow depth over European Russia is above normal than below normal. These results are derived from an examination of 60 years (1936–1995) of winter snow depth data and SSTs, and 45 years (1951–1995) of summer precipitation records. The results of this study suggest that winter snow depth over the western rather than the eastern portion of Eurasia is critical to Southeast Asian summer monsoon rainfall and eastern tropical Pacific SSTs during the following seasons. Copyright © 2001 Royal Meteorological Society
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".