Use of receiver functions in wide-angle controlled-source crustal data sets
Bibliographic record
Abstract
First-arrival waveforms remain underutilized in crustal refraction—reflection seismology by mostly reducing them to traveltime picks. However, as in earthquake seismology, the waveforms also contain important information about shallow near-receiver structures. We illustrate the use of three-component waveform analysis on the records from the ACCRETE wide-angle data set (SE Alaska and British Columbia; 1994), apply the Receiver Function (RF) methodology to the codas of P-wave arrivals, and draw two important conclusions. First, the P-wave polarization azimuths are found to be controlled by the near-receiver structures and virtually unrelated to the source—receiver backazimuths, from which they deviate by up to ∼40°. This observation might be important for studies of anisotropy and also for earthquake RF studies. Second, after correcting for the polarization azimuths, clear P/S mode conversions are reliably detected within 80–400 ms following the primary arrivals. The conversions are interpreted as originating at the base of the sedimentary cover of the fjord channel. In most cases, imaging of the basement requires only several records; however, notable exceptions are also found and interpreted as caused by multipathing, localized scattering, and onsets of crustal and Moho reflections. The ACCRETE example shows that RF methodology could be useful for constraining sediment thickness and deriving P- and S-wave receiver statics in land refraction surveys where collocated reflection profiles are not available. In addition, RFs from repeatable controlled sources could be useful for testing and calibration of RF techniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".