Airborne time-domain electromagnetic data for mapping and characterization of the Spiritwood Valley aquifer, Manitoba, Canada
Bibliographic record
Abstract
A helicopter-borne, time-domain electromagnetic survey was flown over a 1062 km2 area of the Spiritwood Valley in southern Manitoba. The objective was to test the effectiveness of commer-cial, airborne, time-domain electromagnetics for mapping and characterizing buried valley aquifers in the Canadian Prairies. The preliminary data exhibit rich information content, but show some levelling bias and potential limitations of dynamic range or bandwidth. Time slices of the magnetic field decay clearly map the broader Spiritwood Valley in addition to a continuous, incised valley along the broader valley bottom. The data indicate a complex valley morphology with nested scales of valleys, including at least three dis-tinct valley features and multiple possible tributaries. Time-domain electromagnetic response magnitude and decay rates indicate that the fill material within the incised valleys is more resistive than the broader valley fill, consistent with an interpretation of sand and gravel. The electromagnetic data are in excellent agreement with seismic reflection data collected inside the survey block. Further ground-based investiga-tion and data integration is planned. These preliminary results suggest that time-domain electromagnetic surveys have the potential for mapping buried valley aquifers in the Canadian Prairies in far greater detail that any previous techniques.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".