Unravelling the internal structures of salt, by applying anisotropy of magnetic susceptibility to the Carboniferous evaporite deposits of Nova Scotia, Canada
Bibliographic record
Abstract
The mobilisation and intrusion of salt plays a major role in the evolution of basins. Although the geometry and distribution of salt structures can be easily examined, the internal dynamics of salt intrusion are only partially understood. Collecting detailed structural data from outcrop is difficult due to limited exposure, inaccessibility, and poorly preserved visible fabrics. To overcome this crucial impasse in salt tectonics, detailed and high-quality strain data is required from salt outcrops. To obtain structural strain data we have used anisotropy of magnetic susceptibility (AMS) measurements on oriented samples collected from mine and coastal exposures of Carboniferous evaporites in Nova Scotia, Canada. With any AMS study it is important to have a grasp of the magnetic components of the rock. Further magnetic techniques, along with chemical analyses, have been used to better constrain these magnetic properties. Out-of-Phase AMS was also applied for the first time on diamagnetic rocks and rock with very small ferromagnetic fractions to untangle the ferromagnetic fabric from the whole rock. \n \nIt is unusual to find diapiric structures so well exposed as they are on the west coast of Cape Breton, Nova Scotia. These evaporites overlay a predominantly halite diapir core and are surrounded by Carboniferous sediments. Deformation within the gypsum deposits reflect deformation of the underlying halite core of the diapir and the overall structure. Both brittle and ductile deformation fabrics have been recorded within the surrounding sediments and we have observed them imprinted within the evaporite facies. To understand the magnetic fabrics these are detailed and assessed in relation to AMS. 3D Models have been created using aerial drones and photogrammetry to help understand the scalar relationships between fabrics and geological structures related to halokinesis. \n \nPugwash mine offers a perfect opportunity to study diapiric growth structures at a much larger scale. Using 5 maps and 3D photogrammetric models at different depths we can better understand the deformation of the deposit and the 3D geometries formed. Similar experimental methods to those described above have been used to ascertain the strain recorded by the detrital material within the halite samples. This study provides evidence for AMS being a fast, quantitative approach to studying deformed evaporitic deposits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".