Mapping subsurface geological structure using TEMPEST data, McArthur Basin, Northern Territory
Bibliographic record
Abstract
Airborne TEMPEST electromagnetic (EM) and magnetic data was acquired over the Bulman project area in the McArthur Basin to identify the geological environment of stratabound carbonate-hosted Pb-Zn mineralisation. The Late Palaeoproterozoic to Early Mesoproterozoic sedimentary fill of the McArthur Basin in the Bulman area is intruded by Early Mesoproterozoic dolerite dykes and sills. The location of the dykes and sills was mapped using magnetic data. The depth of the intrusives was estimated by mapping resistive basement on Conductivity Depth Transforms (CDTs) generated from the TEMPEST B-field Z-component data. Additionally, a 3D conductivity voxel model was constructed from the CDTs to show the conductivity distribution in rocks.There is no marked conductivity contrast between intrusives and sediments making up the resistive basement. Instead, the resistive basement horizon is interpreted to represent the base of the Cenozoic unconsolidated deposits or part of the Proterozoic sedimentary rocks. In places, the base of a sub-surface conductive zone is interpreted to be the top of the intrusives. The thickness of sediments above the resistive basement is variable, reaching up to 170 metres in the central - eastern part of the study area.3D geological model was constructed to assist in visualising the distribution of interpreted geological units and the tectonic pattern
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".