Geophysical Characterization and MRV Strategy for In-Situ CO2 Mineralization at the CO2 Lock Sam Site, Canada
Bibliographic record
Abstract
Summary CO2 Lock Corp. is developing a novel climate solution through in-situ mineralization of carbon dioxide in brucite-rich ultramafic formations. Its flagship site, Sam, located in British Columbia (Canada), leverages the high reactivity of brucite to permanently convert injected CO2 into stable carbonate minerals. To inform site development, a high-resolution Towed Transient Electromagnetic (tTEM) survey was conducted across the property. This rapid, ground-based resistivity method produced dense geoelectrical imaging of the shallow subsurface, helping to identify fracture networks and competent lithologies. These insights supported the selection of drilling targets and informed preliminary injection zone planning. The upcoming pilot will involve injecting CO2-saturated water into identified fracture zones to test mineralization efficiency. A comprehensive Monitoring, Reporting, and Verification (MRV) framework will be deployed to ensure scientific rigor and traceability. It integrates geophysical, geochemical, and hydrogeological methods to monitor fluid movement, track mineralization progress, and validate permanent CO2 storage. Together, these tools serve dual purposes: optimizing injection design and verifying carbonate formation. The strategy positions the Sam site as a scientifically robust, scalable model for CO2 sequestration, advancing CO2 Lock’s mission of transparent, permanent, and verifiable climate solutions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".