Paleomagnetic techniques can date speleothems with high concentrations of detrital material
Bibliographic record
Abstract
Abstract The U-series dating of young and ‘dirty’ speleothems is challenging due to difficulties in assessing the isotopic composition of detrital contaminants and the low-abundance of 230Th generated in situ. Here we propose a new dating approach based on the comparison of a speleothem’s paleomagnetic directions to reference curves from global paleomagnetic reconstructions. This approach is demonstrated on a stalagmite collected from the Soprador do Carvalho cave in the Central Region of Portugal. A radioisotopic age model, built using four U-series ages and three 14C, suggests relatively steady carbonate precipitation from ~ 5760 BCE until ~ 1920 CE. Forty-five 6 mm-thick subsamples were analyzed using alternating field and thermal demagnetization protocols, providing well-defined, primary magnetic directions. An age model of the stalagmite was obtained by fitting its paleomagnetic record with the reference paleosecular variation curves obtained by previous paleo-reconstruction models, applying statistical bootstrapping analysis to define their best fit. The resulting age models fit closely with the radioisotopic age model but provide a significantly higher time resolution. We reach the same conclusion when applying this approach to another stalagmite from the Algarve region of Portugal. Our approach thus appears a promising alternative to date young speleothems with high detrital contents.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".