Partial anhysteretic remanent magnetization in magnetite 1. Additivity
Bibliographic record
Abstract
We have tested the additivity of partial anhysteretic remanent magnetization (pARM) for suites of eight synthetic magnetites with mean grain sizes from 65 nm to 18 μm and 18 natural samples including lake sediments, oceanic and continental volcanic rocks, gabbros, and granites. In both synthetic and natural sample suites, domain states inferred from hysteresis and other magnetic properties vary from single‐domain (SD) through pseudosingle‐domain (PSD) to multidomain (MD). For each sample, total ARM intensity was compared with sums of partial ARMs of three different types: four conjugate pairs of parallel pARMs; four pairs of perpendicular pARMs; and one set of five neighboring parallel pARMs. In each case, the intervals of alternating field (AF) over which a steady field H was applied to produce the partial ARMs are nonoverlapping and cover the entire AF range (0–100 mT) used to produce the total ARM. Additivity of partial ARMs was verified to better than ±3% for all the samples, whatever the domain state (SD, PSD, and MD) or composition (ranging from pure magnetite to x = 0.6 titanomagnetite). The universality of pARM additivity is unexpected because its analog, partial thermoremanent magnetization (pTRM), deviates from ideal behavior as the grain size increases and the domain structure becomes MD. The different behaviors probably result from the fact that pARM is produced at ordinary temperatures over short times, whereas the most intense pTRM is produced at temperatures approaching the Curie point with significant dwell times, promoting such processes as isothermal remanence acquisition, domain nucleation, and domain wall reequilibration. Verification of the law of additivity of pARMs is an encouraging first step toward validating pseudo‐Thellier and other methods of paleointensity determination that use ARM in place of, or in addition to, TRM.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".