Source Estimation for Wavefield Reconstruction Inversion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Wavefield reconstruction inversion is a new approach to waveform based inversion that helps overcome the ‘cycle skipping’ problem. However, like most waveform based inversion methods, wavefield reconstruction inversion also requires good source wavelets. Without correct source wavelets, wavefields cannot be reconstructed correctly and the velocity model cannot be updated correctly neither. In this work, we propose a source estimation method for wavefield reconstruction inversion based on the variable projection method. In this method, we reconstruct wavefields and estimate source wavelets simultaneously by solving an extended least-squares problem, which contains source wavelets. This approach does not increase the computational cost compared to conventional wavefield reconstruction inversion. Numerical results illustrates with our source estimation method we are able to recover source wavelets and obtain inversion results that are comparable to results obtained with true source wavelets.
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.
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 it