Bibliographic record
Abstract
Abstract A seismic line was shot such that the source-ghost effect from two different dynamite source patterns could be compared. Two 15-shot seismic datasets were created that were identical in all respects except that one used 4 kg of explosives in a single 18-m hole, while the other used 2 kg of explosives in each of two 9-m holes. After identical processing, the final stacked sections of the 18-m and 9-m datasets are dramatically different in character and temporal resolution. An f-x spectral analysis of the stacked sections reveals that the 18-m data shows a loss in power and phase coherence from 45 to 58 Hz, while the 9-m data shows a similar effect from 65 to 78 Hz. A spectral notch, centered near 55 Hz, due to a source ghost is suggested as the reason for the lower power in the 18-m dataset. The 9-m data is consistent with a spectral notch at a higher central frequency near 72 Hz. Above its spectral notch, 18-m data shows a reemergence of weak signal that persists to near 80 Hz; the 9 m dataset shows little signal above 65 Hz. Examination of raw shot records shows that these effects are very difficult to observe in field records. Without specialized deghosting, the 9-m dataset shows greater temporal resolution; however, the 18-m dataset has a broader signal bandwidth and is potentially superior.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".