Imaging Crustal Structure along Refraction Profiles Using Multicomponent Recordings of First-Arrival Coda
Bibliographic record
Abstract
In a way similar to receiver function imaging, coda of the first arrivals can be used to constrain crustal structure along controlled-source refraction profiles with multicomponent recording. Stacked cross-correlations of the radial and vertical components of recordings from three peaceful nuclear explosions of the 3850-km long profile QUARTZ (Russia) exhibit good correlation with the depth to the basement and provide a horizontal resolution level close to recording station spacing (10-15 km). The results also suggest high (∼0.35-0.4) average Poisson's ratios within the sediments. When applied to other multicomponent long-range refraction profiles, this approach could provide a simple and inexpensive way to constrain the structure of the upper crust that is required for interpretation of the deeper structures and that cannot be constrained by other means. Most importantly, reverberations within the sedimentary column appear to account for much of the observed complexity of the first-arrival waveforms, and therefore, such reverberations should be taken into account in the interpretations of seismic scattering from within the mantle. Manuscript received 24 January 2002.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".