Statistical analysis of the 2010 <i>M</i> <sub>W</sub> 7.1 Darfield Earthquake aftershock sequence
Bibliographic record
Abstract
Abstract Statistical properties of the aftershock sequence of the M W 7.1 Darfield (Canterbury, New Zealand) earthquake are studied. The sequence exhibits rich scaling behaviour in magnitude and aftershock decay rates. In particular, we observe a marked variability in the frequency‐magnitude statistics in space, between early and late times after the mainshock and over different magnitude ranges. The mainshock triggered two large earthquakes (22 February 2011 M W 6.2 Christchurch earthquake and 13 June 2011 M W 6.0 earthquake) that occurred later in the sequence and generated their own aftershock sequences. The frequency‐magnitude statistics of the sequences are modelled using the Gutenberg–Richter scaling relation. We also study the difference between the magnitudes of the largest recorded aftershocks and the mainshock. This is analysed and discussed using the modified Båth law. In this context we consider the M W 6.2 Christchurch and 13 June 2011 M W 6.0 earthquakes as the largest aftershocks of the Darfield mainshock. It is also observed that the aftershock decay rates can be approximated by the modified Omori law. The obtained results indicate that the aftershock sequence exhibits self‐similarity in both magnitude and time.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".