Results of a baseline magnetometric resistivity survey at the Field Research Station, Alberta
Bibliographic record
Abstract
With the magnetometric resistivity method (MMR), electrical property contrasts in the ground are obtained from the measure of the magnetic field induced by a galvanic source. Due to the fact that the measurements are done with a magnetic sensor, MMR offers many advantages for monitoring: easier deployment in boreholes (no contact needed) and problems related to electrode installation and corrosion are avoided, also the problem of noise in conductive media is reduced because the magnetic field is a function of current density and not conductivity. The Field Research Station (FRS) is an experimental site operated by the Containment and Monitoring Institute of Carbon Management Canada where are controlled CO2 release experiment is planned for the next 5 years. A preliminary numerical study showed that MMR is suitable for monitoring a CO2 plume at the FRS. In this contribution, we present the results of a baseline survey conducted at the FRS. To our knowledge, this experiment is the first field application of MMR for CO2 monitoring. The aim of the survey was to evaluate the noise conditions at the site and determine the optimal data acquisition parameters, in addition to providing baseline data for a monitoring program.
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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) | 0.001 | 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".