Enhancing predictability by increasing nonlinearity in ENSO and Lorenz systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. The presence of nonlinear terms in the governing equations of a dynamical system usually leads to the loss of predictability, e.g. in numerical weather prediction. However, for the El Niño-Southern Oscillation (ENSO) phenomenon, in an intermediate coupled equatorial Pacific model run under the 1961–1975 and the 1981–1995 climatologies, the latter climatology led to longer-period oscillations, thus greater predictability. In the Lorenz (1963) 3-component chaos system, by adjusting the model parameters to increase the nonlinearity of the system, a similar increase in predictability was found. Thus in the ENSO and Lorenz systems, enhanced nonlinearity from changes in the governing equations could produce longer period oscillations with increased predictability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it