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A lock-in model for the complex Matuyama-Brunhes boundary record of the loess/palaeosol sequence at Lingtai (Central Chinese Loess Plateau)

2003· article· en· W2157308568 on OpenAlexaff
Simo Spassov, Friedrich Heller, Michael Evans, L. P. Yue, Tilo von Dobeneck

Bibliographic record

VenueGeophysical Journal International · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyLoessPaleosolNatural remanent magnetizationMagnetostratigraphyPaleontologyRemanenceGlacial periodGeomagnetic reversalSedimentary rockHorizonPedogenesisDiagenesisMineralogyGeochemistryPaleomagnetismMagnetizationSoil scienceGeometrySoil water

Abstract

fetched live from OpenAlex

In most marine sedimentary records, the Matuyama-Brunhes boundary (MBB) has been found in interglacial oxygen isotope stage 19. In the magnetostratigraphic records of most Chinese loess/palaeosol profiles the MBB is located in loess layer L8, which was deposited during a glacial period. The MBB at Lingtai (central Chinese Loess Plateau) also occurs in L8 and is characterized by multiple polarity flips. The natural remanent magnetization is mainly carried by two coexisting components. The higher coercivity (harder) component dominates in loess layers and is thought to be of detrital origin. The lower coercivity (softer) component prevails in palaeosols and was most probably formed in situ by (bio-)chemical processes. A lock-in model for the Lingtai MBB record has been developed by extending the lithologically controlled PDRM model of Bleil & von Dobeneck (1999). It assumes two lock-in zones. The NRM of the magnetically harder component is physically locked by consolidation shortly after loess deposition, whereas the softer component is formed at greater depth by pedogenesis and acquires a chemical remanent magnetization of younger age. At polarity boundaries, grains carrying reversed and normal directions may therefore occur together within a single horizon. The model uses ARM coercivity spectra to estimate the relative contributions of the two components. It is able to explain the observed rapid multiple polarity flips and low magnetization intensities as well as the stratigraphic shift of the Lingtai MBB with respect to the marine records.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.295
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations83
Published2003
Admission routes1
Has abstractyes

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