Qualitative geophysical interpretation of the Sudbury Structure
Bibliographic record
Abstract
Abstract The Sudbury Structure is one of the most studied geologic structures in the world due to its enigmatic nature and mineral wealth. The available geologic work from the literature and mining industry operations accumulated for more than a century was recently assessed and compiled into a bedrock geologic map. Most regional geophysical investigations of the Sudbury Structure have been quantitative — modeling and depth estimation without a clear definition of surface control. Airborne total magnetic intensity data over the Sudbury Structure were compiled, processed, and interpreted, to define magnetic stratigraphy boundaries and near-surface lineaments. Traditional directional and normalized derivatives were computed to enhance the high-frequency information in the magnetic field. Available airborne frequency-domain electromagnetic (EM) data were also interactively interpreted along profiles and in a gridded format to isolate conductive structures. On-screen geographic information system-based information extraction from multiple derivatives was used to interpret the magnetic contacts, dykes, and lineaments. The magnetic interpretation was compared with published bedrock maps of the Sudbury Structure. Magnetic contacts based on the qualitative classification of the magnetic texture did not always correspond to the geologic boundaries on the existing maps. Some magnetic lineaments corresponded with well-defined geologic structures, some were further extensions of partially mapped structures, and others are newly identified linear structures. Conductive locations identified from the EM profiles were probably due to responses from conductive ore bodies, faults, dykes, lithological contacts, and cultural objects.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".