Chapter 9: Integrated Geologic-Geophysical Interpretation of District-Scale Structural Frameworks: Systematic Approaches for Targeting Mineralizing Systems
Bibliographic record
Abstract
Abstract The integrated interpretation of aeromagnetic data is a key exploration tool to define the concealed, potentially prospective geology that we plan to explore. It helps define the district-scale morphology of structural networks and predict which structures may be associated with the formation of mineral deposits. Aeromagnetic data is particularly useful in guiding geologic mapping, exploration targeting, and strategy because the data available is usually broad, geologic processes and features are normally well imaged in the data, and it is relatively cheap to acquire and process. A foundation to the interpretation of the geophysical data is that the interpreter should be a geoscientist familiar with the geology of the area in question, maximizing the integration of geologic knowledge of the area into the interpretation product. The interpreter must think geologically when building the interpretation, drawing on the parallels between aeromagnetic interpretation and geologic mapping/air photo interpretation. Geologic mapping observations have direct parallels in aeromagnetic interpretation (e.g., lithology, structure, alteration). The interpretation process is outlined using the Lake Lefroy region, Western Australia, including form line construction, identification of magnetic rock units, domain definition, data set integration, definition of structural elements, lithological definition, interpretation of the structural framework, and evaluation of the interpretation. Case studies are then provided at a range of scales from the Pine Creek inlier in northern Australia, the Superior province in eastern Canada, and the Zambian Copperbelt Northwest province to illustrate the connection between the interpretations and exploration targeting. The final integrated interpretation is a supplement to outcrop maps, not a competitor. The purpose is to generate a structural and lithological framework that combines the geophysical data of different types with the mapped geology, which can be interrogated by mineralization models over a much wider area than can be achieved if structural elements and lithology are restricted to areas of outcrop.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".