Recovery of the Alberta Basin Sedimentary Structures in Southern‐Central Alberta Using Nonlinear Inversions of Receiver Functions
Bibliographic record
Abstract
Abstract Secondary converted waves from receiver functions are highly sensitive to physical properties below the Earth's surface. When modeled properly, the waveforms of converted waves offer direct constraints on the impedance contrast, depth, and P‐to‐S velocity ratio pertaining to sedimentary, crustal and mantle interfaces. In this study we introduce a nonlinear waveform inversion algorithm that matches the first 5 s of receiver functions recorded in the Alberta Basin within the Western Canada Sedimentary Basin (WCSB). Our algorithm searches for the optimal thickness of the sedimentary cover and shear velocities of appropriately selected layers within and below it. Combining inversions with forward simulations, we determine the supracrustal stratigraphy from 80 regional broadband seismic stations in the WCSB. The inverted models show east tapering sedimentary layers with their thicknesses ranging from ∼6 km beneath the foothills of the Canadian Rocky Mountains to 3–4 km beneath the Alberta Basin. This finding is consistent with the sedimentary strata determined from regional well‐logging data. The sedimentary layer contains low velocity zones of variable thicknesses and amplitudes that, depending on the locations, may be caused by mechanisms involving deposition, composition or deformation history. Our shear velocity models near the top of the basement complement the existing sonic‐logs or single component seismic data and offer new constraints on the subsidence history of the WCSB. The resolved range of depths (0–14 km) effectively bridges the gap between the vertical scales of well logging (0–6 km) and those of traditional broadband analysis (>10 km) involving receiver functions and surface waves.
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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 | 0.000 | 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".