Magnetic characterization using a three-dimensional hysteresis projection, illustrated with a study of limestones
Bibliographic record
Abstract
Limestones provide an important source of palaeomagnetic information despite their low content of submicroscopic remanence-bearing minerals. The chief sources of these minerals are thought to be clastic volcanic magnetite and titanomagnetite, and organic magnetite, the latter mostly from bacterial sources. Chemically remagnetized limestones carry magnetite or pyrrhotite. Three hysteresis properties prove useful in identifying and characterizing these mineralogical influences on limestones: the ratio of zero-field maximum remanence to saturation remanence (Mr/Ms) in an applied field, coercivity of remanence (Bcr) and coercivity (Bc). To a lesser extent Kf/Ms may be useful, where Kf is the ferrimagnetic susceptibility. Traditionally, these have been plotted on a combination of 2-D graphs that of necessity only preserve two variables (Day et al. 1977; Wasilewski 1973). However, we found that magnetic discrimination and characterization of the limestones was much easier on a three-axis hysteresis projection that preserves the values of Bcr, Bc and Mr/Ms as independent variables. Using logarithmic scales, the regression surfaces through the data become almost planar and distinguish pelagic, shallow marine, shelf and remagnetized limestones on the basis of the slope and intercept of the associated regression surface. Clearly, there are sensitive sedimentological, geochemical or organic influences that dictate the magnetic mineralogy through sedimentary environment. Moreover, the 3-D plot of hysteresis criteria affords easy recognition of remagnetized limestones and may permit the rejection of material unsuitable for palaeomagnetic study. The 3-D hysteresis projection may be useful for the characterization of other rocks and magnetic materials
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".