Feasibility testing of simultaneous source elastic full-waveform inversion
Bibliographic record
Abstract
The suitability of simultaneous sources in elastic full waveform inversion is tested through a series of synthetic inversions. Point spread functions, representing the action of the Hessian on a model perturbation, are employed to assess the resolution and parameter trade-offs of simultaneous source full waveform inversion relative to its conventional counterpart. The expected value of point spread functions in simultaneous source full waveform inversion approach those obtained from sequential source waveform inversion as the number of random realizations increases. The observation suggests that the resolving power and parameter trade-offs of both inversion schemes are comparable if cross-talk artefacts are attenuated. A series of synthetic inversions demonstrate that simultaneous source inversion is able to attain comparable inversion results to full waveform inversion while requiring orders of magnitude fewer computational resources. Presentation Date: Thursday, September 28, 2017 Start Time: 11:25 AM Location: 371A Presentation Type: ORAL
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".