Joint transmission and reflection traveltime tomography in imaging permafrost and thermokarst lakes in Northwest Territories, Canada
Bibliographic record
Abstract
We propose an application of joint tomographic inversion using both transmitted and reflected arrivals to map velocity structures in thick permafrost areas of the Mackenzie Delta, Northwest Territories of Canada. Our tomography algorithm combines a grid-based solver of the eikonal equation, Huygens' principle, and the adjoint method. The grid-based solver assigns a traveltime to each grid point and avoids the shadow-zone problem in classical ray tracing and is well-adapted for parallelization. The adjoint method used in the inversion provides the gradient of a given objective function without explicitly estimating the Fréchet derivative matrix. When combined with Huygens' principle, the tomographic inversion can simultaneously use first and later arrivals to optimize a final velocity model. We first demonstrate the performance of the joint tomography algorithm on a two-dimensional synthetic model with velocity variations typical of permafrost. The method is then applied to a 2D seismic survey covering over 20 km with offsets up to 4 km, acquired in the Mackenzie Delta. The subsurface at that location is characterized by a thick permafrost (600 m) comprising high-velocity and low-velocity areas associated with thermokarst lakes. Our results show the potential of the joint tomography in characterizing multiscale heterogeneous velocity structures within the permafrost.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".