Misconception of Waveform Similarity in the Identification of Repeating Earthquakes
Bibliographic record
Abstract
Abstract Identification of repeating earthquakes (repeaters) usually depends on waveform similarity expressed as the corresponding cross‐correlation coefficient (CC) above a prescribed threshold, typically ranging in 0.70–0.98. However, the robustness and effectiveness of such a strategy have rarely been fully examined. In this study, we examine whether CC is a valid proxy for repeater identification through both synthetic and real earthquake experiments. We reveal that CC is controlled by not only the interevent distance but also many other factors, including station azimuth, epicentral distance, and velocity structure. Consequently, CC lacks the resolution in identifying true repeaters. For reliable repeater identification, we should consider the interevent overlap. Specifically, we define an event pair to be true repeaters if their interevent separation is smaller than the source dimension of the larger event. Our results imply that a systematic recheck of previously identified repeaters and associated interpretations/hypotheses may be important and necessary.
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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 | 0.028 | 0.162 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".