Preferred orientation of ferromagnetic phases in rock-forming minerals: insights from magnetic anisotropy of single crystals
Bibliographic record
Abstract
In the early days of paleomagnetism, David Strangway was interested in understanding why igneous rocks are faithful recorders of the Earth’s magnetic field. He recognized that ferromagnetic (s.l.) grains that could be discerned by optical microscopy were too large to carry a stable remanent magnetization, and speculated whether fine-grained, ferromagnetic (s.l.) inclusions or exsolutions in silicate minerals are responsible. When these inclusions or exsolutions are randomly oriented, or the silicate hosts are randomly oriented in a rock, they can be a good recorder of the field. If these minerals, however, show an alignment within the silicate host, and the host is preferentially aligned due to flow structures or deformation, then the paleomagnetic direction and paleointensity could be biased. We examine the magnetic anisotropy arising from the ferromagnetic (s.l.) phases in silicate-host minerals. Single crystals of phyllosilicate, clinopyroxene, and calcite show most consistent ferrimagnetic fabric with relation to the minerals’ crystallographic axes, whereas olivine and feldspar display only a weak relationship. No discernable relationship is found between the ferrimagnetic anisotropy and crystallographic axes for amphibole minerals. Our results have implications when single crystals are being used for either studies of field direction or paleointensity or in cases where silicate minerals have a preferential orientation. Phyllosilicate minerals and pyroxene should be screened for significant magnetic anisotropy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".