Bibliographic record
Abstract
The spatial structure of asymmetries in sea surface temperature (SST) and surface air temperature (SAT) between average El Nino and La Nina events is considered. It is demonstrated that in historical SST and SAT reconstructions, the anomaly spatial pattern that changes sign between El Nino and La Nina events (the ''linear'' signal) strongly resembles that of principal component analysis (PCA) mode 1, while that which does not change sign (the ''nonlinear'' signal) resembles the pattern of PCA mode 2. The linear and nonlinear patterns also strongly resemble the standard deviation and skewness fields, respectively. Furthermore, temporal subsampling of long (130 yr) SST reconstructions suggests that the magnitude of the nonlinear signal and its similarity to PCA mode 2 are functions of the strength of ENSO, as measured by the standard deviation of the PCA mode- 1 time series. Finally, it is found that of several coupled general circulation models (GCMs) considered, the spatial and temporal structure of the El Nino-La Nina asymmetry is captured only by the GFDL R30 model, despite large biases in its covariance structure.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".