Correcting airborne gravity data for overburden thickness: a case study from the Nechako interior plateau, British Columbia
Bibliographic record
Abstract
Large areas of bedrock in Canada, such as in the interior plateau of British Columbia, are covered by a thick glacial overburden. Lateral variations in overburden thickness can create spurious anomalies in gravity data. These anomalies can be of a size and amplitude similar to those associated with mineral bodies and can be mistaken for them. A methodology is introduced that corrects gravity data for changes in overburden thickness through the use of a bedrock topography map created by integrating information from a helicopter transient electromagnetic survey with geological survey data, well water data, and gravel pit locations. The approach is tested for a 68 km × 38 km area in the prospective Nechako interior plateau of British Columbia, Canada. The methodology extends the traditional Bouguer corrections by taking into account the gravitational contribution of the overburden. Results show that the capability of an airborne survey to detect a change in overburden thickness depends primarily on survey line spacing and to a lesser extent on the level of random noise in the gravity data. The bedrock topography correction has the capability of removing the gravitational attraction of overburden for the purpose of revealing, through interpretation, geological structures in the gravity data that originate from the bedrock and are otherwise concealed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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 teacher head, 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".