Geoeffectiveness of X and M Class Solar Flares (SF) and Associated Halo Coronal Mass Ejections (CMEs)
Bibliographic record
Abstract
We studied the geoeffectiveness, the angular width, and the association with solar flares of classes X and M for a set of 262 halo-type coronal mass ejections (CMEs) during solar cycles 23 and 24, covering the period from 1996 to 2019 inclusive. We compiled the minimum Dst values that occurred within 1 to 5 days after the CME onset. We compared the distributions of these Dst values for the following subsets of halo-type CMEs: narrow CMEs (angular width < 60°), medium CMEs (angular width between 60° and 120°), and wide CMEs (angular width > 120°). A halo-type CME is defined as geoeffective if followed by a Dst value lower than -50 nT; moderately geoeffective if the Dst is between -50 nT and -100 nT; strongly geoeffective with Dst values between -100 nT and -200 nT; and severely geoeffective if followed by a Dst value lower than -200 nT (this is already defined in the method section). The analysis of the 262 coronal mass ejections (CMEs) reveals that 14.1% are narrow CMEs, with 11.1% associated with M-class flares and 3% with X-class flares. Of the narrow CMEs, 5.3% were geoeffective. Medium-width CMEs account for 22.9%, also mostly linked to M-class (13.7%) and X-class (9.2%) flares, with 8% geoeffectiveness. Wide CMEs dominate with 63%, with 42.4% originating from M-class flares and 20.6% from X-class flares. Among the wide CMEs, 29.8% were geoeffective. Overall, 43.1% of the CMEs were geoeffective, with a greater contribution from M-class flares. During cycle 23, 48% of M-class flares accompanied by halo CMEs were geoeffective, compared to 62.7% for X-class flares. In cycle 24, the geoeffectiveness of M-class and X-class flares accompanied by halo CMEs was 26.3% and 23.5%, respectively.
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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 | 0.002 |
| 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 | 0.000 | 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".