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Record W4200493938 · doi:10.1029/2021gl096072

3D Joint Inversion of Scanning Magnetic Microscopy Data

2021· article· en· W4200493938 on OpenAlexaff
Zeudia Pastore, Peter G. Lelièvre, S. A. McEnroe, Nathan Church

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsMount Allison University
FundersNorges Teknisk-Naturvitenskapelige Universitet
KeywordsRemanenceNatural remanent magnetizationMagnetizationGeologyMagnetometerMagnetic anomalyRock magnetismMineralogyGeophysicsPhysicsMagnetic field

Abstract

fetched live from OpenAlex

Abstract Scanning magnetic microscopy (SMM) is a modern magnetometry technique that maps the magnetic anomalies resulting from small‐scale variations of remanent magnetization within a sample. This information is vital to understand the origin of rock behavior in laboratory experiments and in larger scale magnetic surveys. To quantify the fine‐scale remanent magnetization, we used 3D magnetic vector inversion to jointly invert SMM data collected both above and below a 5 mm‐thick norite sample from the Bjerkreim‐Sokndal layered intrusion in South Norway. The sample is from an area with a striking remanent aeromagnetic anomaly which shows a minimum of −13,000 nT below background in the high‐resolution helicopter survey. Inversion results confirm bulk remanent magnetization measurements with calculated median magnetization intensities between 79 and 106 A/m and a strong preferred magnetization direction perpendicular to the slab plane. Furthermore, results indicate that the main source of natural remanent magnetization is in the pyroxenes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.088
GPT teacher head0.341
Teacher spread0.253 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations7
Published2021
Admission routes1
Has abstractyes

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