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Record W1969034680 · doi:10.1029/2002gl015597

Thermoremanence and stable memory of single‐domain hematites

2002· article· en· W1969034680 on OpenAlexaff
Özden Özdemir, David J. Dunlop

Bibliographic record

VenueGeophysical Research Letters · 2002
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDemagnetizing fieldMagnetismThermoremanent magnetizationCondensed matter physicsHematiteRock magnetismRemanenceMaterials scienceMagnetizationGrain sizeSingle domainSingle crystalMagnetic domainNuclear magnetic resonanceMagnetic fieldPhysicsMetallurgy

Abstract

fetched live from OpenAlex

We report thermoremanent magnetization (TRM) intensities and thermal demagnetization behavior of seven samples of single‐domain hematite (α Fe 2 O 3 ) with grain sizes between 0.12 and 0.42 μm, before and after zero‐field cycling through the low‐temperature Morin transition (T M ≈ 240 K). TRM was unaffected by 100 mT alternating field demagnetization and by 600°C thermal demagnetization. Most demagnetization occurred between 625°C and the Néel temperature of 680–690°C. The TRM memory recovered after low‐temperature cycling was parallel to the original TRM and equally resistant to thermal demagnetization. TRM and TRM memory of single‐domain hematites are mainly due to the hard spin‐canted magnetism intrinsic to the crystal structure above the Morin transition, and not to the small and softer defect magnetism that survives below T M . However, the defect magnetism may play a role in renucleating the spin‐canted magnetism in a preferred direction during warming through T M . TRM intensities are well predicted by Neél single‐domain theory and increase in almost exact proportion to grain size. Although smaller than TRM intensities of multidomain hematites, single‐domain TRMs are potent sources of remanent magnetic anomalies, particularly for larger grains (10–15 μm), and are likely to be more stable over geological time than multidomain hematite TRMs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.284
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2002
Admission routes1
Has abstractyes

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