Imaging the Nechako Basin, British Columbia, using ambient seismic noise<sup>1</sup>This article is one of a series of papers published in this Special Issue on the theme of <i>New insights in Cordilleran Intermontane geoscience: reducing exploration risk in the mountain pine beetle-affected area, British Columbia</i>.
Bibliographic record
Abstract
The Nechako Basin in British Columbia, Canada is suspected to have hydrocarbon potential. However, it has been a difficult basin to explore because of the presence of Tertiary volcanic outcrop. The volcanic outcrop makes the use of conventional seismic exploration methods difficult owing to a strong velocity inversion at its base. An alternative is the passive source method known as ambient noise surface wave tomography. The method, which examines the high-frequency surface wave field that is obtained from noise analysis, is sensitive to large-scale crustal structure and has been successfully applied to measuring the depths of sedimentary basins. Station-to-station Green’s functions within the basin were estimated by cross-correlating the vertical components of the seismic noise data recorded by 12 POLARIS (Portable Observatories for Lithosphere Analysis and Research Investigating Seismicity) and CNSN (Canadian National Seismgraph Network) seismic stations between September 2006 and November 2007. The resulting Green’s functions were dominated by Rayleigh waves. The dispersion characteristics of the Rayleigh waveforms were measured within the microseismic band. Inversion of the dispersion curves produced 1-D and 2-D thickness models and 2-D group velocity models for the Nechako Basin and its surrounding region. The velocity models indicate two low group velocity structures within the basin that might represent sedimentary packages, and some pockets of high-velocity zones that show the presence of volcanic rocks within and on the basin. The thickness models indicated the presence of about six different velocity layers, in which the average thickness of the basin and the crust are ∼4.8 and 30–34 km, respectively.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".