Bibliographic record
Abstract
The analytical signal method for seismic attenuation (Q) estimation is reviewed and investigated using a 1D surface data model and field VSP data. The error in Q-factor recovery from modelled data using the analytical signal method is better than 7 percent over a range of Q-factors from 25 to 100. The method is applied to the enhanced downgoing P-wave of an offset VSP-survey from Ross Lake, Saskatchewan. The logarithm of the instantaneous-amplitude ratio versus time-increment plot (an internal step in the method) is surprisingly smooth when compared to log spectral ratios of the same data. The depth average of Q is 34 for clastic rocks of the Ross Lake area. This compares to a Q range of 37 to 41 obtained from the drift correction method over a similar depth range in previous work, which is somewhat lower than a Q of 67 obtained from the spectral ratio method. Errors in Q-estimation by the analytical signal method appear to be caused by insufficient moveout compensation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.338 | 0.256 |
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".