3D geophysical inversions of the north‐east Amer Belt and their relationship to the geologic structure
Bibliographic record
Abstract
ABSTRACT The Amer Lake area is located within the Churchill Structural Province in the Kivalliq Region of Nunavut, approximately 160 km north‐west of Baker Lake. Two distinct geophysical‐geological entities are structurally intercalated: an Archean mixed granitoid gneiss – metasedimentary‐metavolcanic basement and the unconformably overlying Paleoproterozoic Amer Group metasediments. From east of Amer Lake stretching toward the south‐west, these two entities form the Amer fold and thrust belt. At the north‐east end of this belt, high‐resolution aeromagnetic data define a distinctive oval shape that has been interpreted as a south‐west trending doubly plunging synform. The outcrop within the interior of this structure is sparse resulting in limited structural data and speculative geological interpretations with multiple geometries possible. The high‐resolution aeromagnetic data compiled through an industry‐government consortium and newly acquired detailed gravity profiles were modelled to provide constraints on the geometry of this synform. We document a geophysical‐geological feedback process whereby the available geological and geophysical data were used to derive constraints on inversion models for the synform. Starting with available limited litho‐structural data the presence of a double plunging synform was directly inferred from the aeromagnetic data. Segments of the aeromagnetic data have 2D morphology and so can be modelled using a simple parametric 2D dipping slab inversion approach. Models of profiles extracted from the aeromagnetic data were used to provide preliminary dip and magnetic susceptibility constraints for the Three Lakes mudstone with iron formation and the Five Mile Lake basalt. Landsat imagery outlined the spatial limits of the stratigraphically underlying, non‐magnetic Ayagaq quartzite. Incorporating these outputs as bounds in the input / reference model for a UBC‐GIF 3D magnetic inversion helped to accentuate the geological structure in the output mesh: an enhanced inversion that incorporates both geological and geophysical constraints. The validity of the resulting inversion model was tested by computing 2D forward models of the gravity profile data. The inversion model generated by this study emphasizes the importance of integrating information from as many knowledge sources as one can find. More trust can be placed on forward and inversion models where there is agreement among all data sets and a coherency of structural style.
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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 | 0.001 |
| 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) | 0.002 | 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".