A lock-in model for the complex Matuyama-Brunhes boundary record of the loess/palaeosol sequence at Lingtai (Central Chinese Loess Plateau)
Bibliographic record
Abstract
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.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".