A Bayesian Approach to Inferring Depositional Ages Applied to a Late Tonian Reference Section in Svalbard
Bibliographic record
Abstract
Increasing application of high precision uranium-lead (U-Pb) and rhenium-osmium (Re-Os) geochronology to the ancient geological record has resulted in massive improvement in age control and calibration of key Proterozoic stratigraphic successions and events. Nevertheless, some successions and time intervals remain poorly dated. Insufficient age constraints are particularly problematic for successions that are otherwise rich in geochemical, fossil, or other data with high potential to illuminate our understanding of Proterozoic Earth history. The latter Tonian succession in northeastern Svalbard is one such example. The ca. 820–740 Ma Akademikerbreen and lowermost Polarisbreen groups contain important microfossils and well-established carbon- and strontium-isotopic records, but they remain poorly dated. Here we use radioisotopic dates correlated from other Tonian successions across the globe using carbon isotope chemostratigraphy to calibrate a Tonian composite section in Svalbard by integrating Bayesian inference with a simple 1D thermal subsidence model. This approach allows us to assign realistic ages and uncertainties to all stratigraphic heights in a Akademikerbreen-lower Polarisbreen composite reference section. For example, the Bayesian age-height model yields ages for the onset and end of the Bitter Springs negative carbon isotope anomaly of 808.7 +3.3/−3.5 Ma and 801.9 +3.2/−3.3 Ma, respectively, and a total duration of 6.9 ± 0.2 Ma. These age and duration estimates can be applied to calibrate other Tonian successions that capture the Bitter Springs anomaly assuming that this anomaly is globally correlative.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".