Preliminary Characterization of Submarine Basalt Magnetic Mineralogy Using Amplitude‐Dependence of Magnetic Susceptibility
Bibliographic record
Abstract
Abstract The past ∼200 million years of Earth's geomagnetic field behavior have been recorded within oceanic basalts, many of which are only accessible via scientific ocean drilling. Obtaining the best possible paleomagnetic measurements from such valuable samples requires an a priori understanding of their magnetic mineralogies when choosing the most appropriate protocol for stepwise demagnetization experiments (either alternating field or thermal). Here, we present a quick, and non‐destructive method that utilizes the amplitude‐dependence of magnetic susceptibility to screen submarine basalts prior to choosing a demagnetization protocol, whenever conducting a pilot study or other detailed rock‐magnetic characterization is not possible. We demonstrate this method using samples acquired during International Ocean Discovery Program Expedition 391. Our approach is rooted in the observation that amplitude‐dependent magnetic susceptibility is observed in basalt samples whose dominant magnetic carrier is multidomain titanomagnetite (∼TM 60–65 , (Ti 0.60–0.65 Fe 0.35–0.40 )Fe 2 O 4 ). Samples with low Ti contents within titanomagnetite or samples that have experienced a high degree of oxidative weathering do not display appreciable amplitude dependence. Due to their low Curie temperatures, basalts that possess amplitude‐dependence should ideally be demagnetized either using alternating fields or via finely‐spaced thermal demagnetization heating steps below 300°C. Our screening method can enhance the success rate of paleomagnetic studies of oceanic basalt samples.
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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) | 0.001 | 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".