Interpolated multichannel singular spectrum analysis: A reconstruction method that honors true trace coordinates
Bibliographic record
Abstract
ABSTRACT The multichannel singular spectrum analysis (MSSA) reconstruction algorithm denoises and reconstructs seismic traces on a regular grid. We have developed a modified version of MSSA that can cope with denoising and reconstruction of traces with irregular coordinates. The proposed method, interpolated multichannel singular spectrum analysis (I-MSSA), connects off-the-grid observations to the desired gridded data via a linear interpolation operator. The algorithm consists of two steps. In the first step, we use the steepest-descent method to estimate the gridded data that honors off-the-grid observations. The second step guarantees convergence to a solution by applying the MSSA filter to the gridded data. The final solution is the reconstructed volume that honors off-the-grid observations. We use the algorithm to process synthetic and field data. We also provide an application in which 3D prestack data corresponding to an orthogonal survey are fully reconstructed using cross-spread gathers. We use I-MSSA to restore each subset individually. The output is a complete seismic volume described in a regular common-midpoint grid.
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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 | 0.001 |
| 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 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".