Bibliographic record
Abstract
Abstract Several extensions of the concept of acoustic impedance (AI) to oblique incidence exist and are known as elastic impedances (EI). These quantities are constructed by heuristic integrations of reflectivity series but still involve approximations and do not represent a unique medium property. Nevertheless, for unambiguous interpretation, it is desirable to have an EI that would (1) be a mechanical property of the medium and (2) yield exact reflection coefficients at all angles of incidence. Here, such a definition is given for P- and/or SV-wave propagation in an arbitrary isotropic medium. The exact elastic P/SV impedance is a matrix quantity and represents the differential operator relating the stress and strain boundary conditions. With the use of the matrix form of the reflectivity problem, no approximations are required for accurate modeling of reflection (P/P and SV/SV) and mode-conversion (P/SV and SV/P) coefficients at all angles and for any contrasts in elastic properties. The matrix EI can be computed from real well logs and inverted from ray-parameter-dependent seismic reflectivity. Known limiting cases of P- and S-wave acoustic impedances are accurately reproduced and the approach also allows the extension of the concept of impedance to an attenuative medium. The matrix impedance readily lends itself to inversion with uncertainties typical of the standard acoustic-impedance inversion problem.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".