Introduction to this special section: Multicomponent seismic
Bibliographic record
Abstract
A seismic source excites a rich variety of elastic waves in the Earth, so it seems reasonable to try to use them all to create a more compelling picture of the subsurface. While P-wave imaging has been enormously successful in this regard, there are conditions when it is less so. But, the demands of energy discovery and recovery require an increasingly comprehensive portrayal of reservoir lithologies, stresses, fractures, and fluids. The multicomponent seismic method is a superset of conventional seismic technology and has the potential to answer to some of these demands. Recording horizontal motion, as well as vertical vibrations and pressures, allows further capturing of the full seismic wavefield, and the additional resultant pictures can provide greater comprehension of subsurface properties, fluids, and their changes. We might liken this to a more complete conversation with “loud” waves (P-waves arriving first with high amplitudes) and “shy” waves (S-waves with lower voices and a more complicated message).
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 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) | 0.005 | 0.004 |
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; both teacher heads agree on what is shown here.
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".