Connectivity and Rotation of Entropicly Defined Clusters as a Measure of Hurricane and Tornado State
Bibliographic record
Abstract
A statistical physical model of the two basic properties of clusters within a hurricane their convectivity and rotation - reveals a relationship for the time evolution of a hurricane. Non-doppler data from NEXRAD surface radar imagery, of Hurricane Irma transiting over Florida, is decomposed into unique clusters based on an annealing process using entropy and energy differences between pixels. Application of the concept of entropic forces between a cluster’s pixels provides an estimate of the radial velocity of each cluster by application of Stokes’ theorem. The ratio of the characteristic rotation and convectivity, associated with radial flow, integrated over the extent of the hurricane, closely tracks the hurricane’s state, providing more time resolution than aircraft sorties alone allow. It is concluded that monitoring the rotational and convective state, in conjunction with the size of a cluster, is capable of quickly providing forecasters and others with changes in a hurricane’s state. It is also shown that entropic tornado state can be similarly described in terms of convectivity and rotation rate.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".