Nonlinear atmospheric variability in the winter northeast Pacific associated with the Madden‐Julian oscillation
Bibliographic record
Abstract
The Madden‐Julian Oscillation (MJO), the primary mode of large‐scale intraseasonal variability in the tropics, is known to relate to the mid‐latitude atmospheric variability. Using neural network techniques, a nonlinear projection of the MJO onto the precipitation and 200‐hPa wind anomalies in the northeast Pacific during January–March shows asymmetric atmospheric patterns associated with different phases of the MJO. For precipitation, the strength of the nonlinear effect to the linear effect was 0.94 (in terms of the squared anomalies and averaged over all phases of the MJO), indicating strong nonlinearity, while for the 200‐hPa wind, the ratio was 0.55, indicating moderate nonlinearity. In general, anomalous winds blowing from the north or from land were associated with negative precipitation anomalies, while winds from the south or from the open ocean, with positive precipitation anomalies. The nonlinear effects generally induced positive precipitation anomalies during all phases of the MJO.
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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 | 0.000 | 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) | 0.001 | 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".