2017 U.S. Geological Survey/BC Hydro seismic data recorded at three dam sites on Vancouver Island, British Columbia, Canada
Bibliographic record
Abstract
In May 2017, we acquired high-resolution seismic profiles near three dam sites (Strathcona, Laodre and John Hart dams) located on Vancouver Island, British Columbia, Canada. Our goal was to measure seismic velocities (particularly Vs) at each dam site using body and surface waves. The data were analyzed using refraction tomography and multi-channel analysis of surface waves (MASW), especially in the upper 30 m of the subsurface. The analyzed data are presented in a separate report (Catchings and others, in review). We also recorded one hour of ambient noise (passive-source) data along most of the same profiles. This work was completed under the authority of a 2011 agreement relating to scientific and technical cooperation in the earth sciences between the USGS-Department of the Interior of the United States and British Columbia Hydro and Power Authority of British Columbia, Canada. Acknowledgements We thank Keith Galvin, Freddie Jackson, Nicholas Ogasa, Brandon Smythe, Steve Watson, Alan Yong, and Edward Zhang for field assistance in acquiring the data. We thank Maria Garcia and Ray Chickite for medical assistance, and we thank several additional BC Hydro staff for field and office support. We thank Robert Fornasier and Jane Meyer for logistical and administrative support. Reference Cited Catchings, R.D., Addo, K.O., Goldman, M.R., Chan, J.H., Sickler, R.R., and Criley, C.J., in review, Seismic velocities and 2-D structural variations at three BC Hydro dam sites, Vancouver Island, British Columbia, Canada: U.S. Geological Survey Open-File Report 201X-XXXX, XX pp.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".