Bibliographic record
Abstract
Magnetites with sizes from 1 μm to 135 μm were cooled in zero field and their magnetizations M(T) measured continuously. M(T) changed reversibly in cooling from T0 = 300 K to 200 K, and in subsidiary warming‐cooling cycles Ti → T0 → Ti for any Ti. Changes in M(T) in cooling from 200 K to 130 K were largely irreversible due to decreasing magnetocrystalline anisotropy which promotes wall unpinning and domain nucleation. Low‐temperature demagnetization (LTD) is almost complete by 130 K in 20–135 μm magnetites but in 1–14 μm magnetites further LTD occurs on cooling to 120 K as magnetocrystalline easy axes change and domains reorganize at the Verwey transition. The observed irreversible changes are the basis of stepwise LTD as a method of paleomagnetic “cleaning.” Decrements ΔM in remanence due to cooling are most accurately measured at T0, requiring a set of warming‐cooling cycles Ti → T0 → Ti. A less accurate method, continuous LTD, measures decrements M(Ti) − M(Ti−1) from the main cooling curve below 200 K, without intermediate warming‐cooling cycles; this requires remanence measurements at Ti < T0. Stepwise or continuous LTD curves M(Ti) discriminate among remanence types and grain sizes. The signal of finer (PSD) grains is enhanced compared to coarser (MD) grains. Analogous to the Lowrie and Fuller [1971] test, the inverse thermoremanence (ITRM) of 1–14 μm grains is harder to stepwise LTD than saturation remanence (SIRM), while anhysteretic remanence (ARM) is harder than either; for 20–135 μm multidomain grains, ITRM is softer than SIRM.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".