Exploring the near surface geothermal structure at Mt. Meager, British Columbia, Canada
Bibliographic record
Abstract
Mount Meager is located ~150 km north of Vancouver, British Columbia Canada, and is a part of the Garibaldi volcanic belt. Exploration at Mount Meager for geothermal energy resources has been ongoing since 1974 and has shown, based on well data, that there is a permeable zone at a depth of 1200-1600 m and that the reservoir has a temperature of 270 °C near 2500 m depth. In this study, we have utilized recordings and related information from a new network of 84 audio-magnetotelluric (AMT) stations collected during the summer of 2019 plus 37 stations from previous studies to investigate the geothermal potential of the area around Mount Meager and Pylon peak. We used Phoenix Geophysics’ MTU-5C recording equipment and their proprietary software for data processing, separating extensive noise from the signal, to calculate the components of the natural electrical and magnetic signals in the frequency domain. After manual processing and editing, the data showed good quality in the frequency range of 1 to 1000 Hz. The ModEM inversion algorithm (Egbert and Kelbert, 2012) was then used to model the data. Modelling started using a coarse grid mesh with different starting resistivities, and then a finer grid size and topography was added to refine the model. The preliminary result of this 3D inversion defines the shape and location of conductors in the study area. The results show a conductor at a depth 2000 m located to the southwest of Mount Meager. Comparison of the 3D model and the geological setting of the area demonstrated that this conductor shallows toward the southern portion of the No-good Fault.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".