Extent of Low‐Angle Normal Slip in the 2010 El Mayor‐Cucapah (Mexico) Earthquake From Differential Lidar
Bibliographic record
Abstract
Abstract We investigate the 4 April 2010 Mw 7.2 El Mayor‐Cucapah (Mexico) earthquake using three‐dimensional surface deformation computed from preevent and postevent airborne lidar topography. By profiling the E‐W, N‐S, and vertical displacement fields at densely sampled (∼300 m) intervals along the multisegment rupture and computing fault offsets in each component, we map the slip vector along strike. Because the computed slip vectors must lie on the plane of the fault, whose local strike is known, we calculate how fault dip changes along the rupture. A principal goal is to resolve the discrepancy between field‐based inferences of widespread low‐angle (<30°) oblique‐normal slip beneath the Sierra Cucapah, and geodetic and/or seismological models which support steeper (50°–75°) faulting in this area. Our results confirm that low‐angle slip occurred along a short (∼2 km) stretch of the Paso Superior fault—where the three‐dimensional rupture trace is also best fit by gently inclined planes—as well as along shorter (∼1 km) section of the Paso Inferior fault. We also characterize an ∼8‐km fault crossing the Puerta accommodation zone as dipping ∼60°NE with slip of ∼2 m. These results indicate that within the northern Sierra Cucapah, deep‐seated rupture of steep faults (resolved by coarse geodetic models) transfers at shallower depths onto low‐angle structures. We also observe a statistically significant positive correlation between fault dip and slip, with slip pronounced along steep sections of fault and inhibited along low‐angle sections. This highlights the important role of local structural fabric in controlling the surface expression of large earthquakes.
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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 | 0.000 |
| 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".