Bibliographic record
Abstract
From the statistics of solar radio bursts, we learn that we can discriminate between three diagnostic regimes: (i) the incoherent regime where the radio burst flux is essentially proportional to the flare volume (with a power law slope of ), as it occurs for gyroemission, gyroresonance emission, gyrosynchrotron emission; (ii) the coherent regime that implies a nonlinear scaling between the radio flux and the flare volume ; as it occurs for the electron beam instability, the loss-cone instability, or maser emission; and (iii) the exponential regime that does not display a power law function, but rather an exponential cutoff as expected for random noise distributions. Thus, the power law slopes offer a useful diagnostic to verify the flux–volume scaling law and to discriminate between coherent and incoherent radio emission processes, as well as to distinguish between SOC processes and non-SOC processes. An additional diagnostic comes from the inertial range of power law fits: SOC-related power law size distributions should extend over multiple decades, while power law ranges of less than one decade are most likely not related to SOC processes.
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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".