Evaluating Late Holocene radiocarbon-based chronologies by matching palaeomagnetic secular variations to geomagnetic field models: an example from Lake Kalimpaa (Sulawesi, Indonesia)
Bibliographic record
Abstract
Abstract Palaeomagnetic and palaeoenvironmental data from Indonesia and particularly from the Island of Sulawesi are scarce and exact dating has turned out to be a challenge in many archives from this region. Here we outline difficulties in radiocarbon dating of the palaeoenvironmental record from Lake Kalimpaa, Sulawesi, Indonesia. These difficulties demand the integration of additional parameters to obtain a reliable chronology for this record. Thus, we compare the palaeomagnetic secular variation data from this record with the CALS3k.4 spherical harmonic geomagnetic model of the 0–3 ka field ( Korte & Constable 2011 ). The resulting age–depth model for the Lake Kalimpaa sequence provides a profound basis for further multi-proxy investigations on this record. For the first time, high-resolution palaeomagnetic secular variation data continuously spanning the past 1300 years are presented for this region, which complement existing records with lower temporal resolution or records missing the top-most sections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".