Bibliographic record
Abstract
Summary A 3D modelling technique, called Rayleigh-Sommerfeld modelling, is described as an alternative to Kirchhoff modelling. Rayleigh-Sommerfeld modelling, when applied using a forward Born approximation, is shown to be the familiar phase-shift migration running in reverse. Compared to the Kirchhoff method, Rayleigh-Sommerfeld is much faster, especially on large datasets, but produces a similar response. Rayleigh-Sommerfeld is used to create an exhaustive 3D synthetic dataset which will be used for 3D migration testing. Such an exhaustive dataset, defined as having no spatial aliasing in either source or receiver gathers, can be extremely large and the efficiency of Rayleigh-Sommerfeld modelling is required to create one. The model created is the response of three horizontal reflectors embedded in a () vz medium. Consisting of 1681 source gathers, each having 1681 receivers, it is shown to be very high frequency and to contain both specular reflections and diffractions. Example 3D shot record migrations demonstrate the fidelity of the model and the high resolution of prestack migration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".