U-Pb Dating of Fossils and Calcite: dating the Sedimentary and Paleontological record
Bibliographic record
Abstract
We studied the feasibility of using laser ablation inductively coupled plasma mass spectrometry (LA–ICPMS) for U–Pb dating of fossils (vertebrate-invertebrate) and pedogenic calcite. U–Pb dating of hydrogenic and fossil material can be challenging because samples often contain low U levels and variable amounts of non-radiogenic Pb. Our improved processing methods (UtilChron) give accurate U–Pb ages for low U samples. Line scans using LA–ICPMS provide the widest range of ratios available for defining the radiogenic to common Pb mixing line, hence the best age estimate for calcite and fossil material. For example, the first accurate U–Pb age on fossilized soft tissue, yielded an age of 3.16 ± 0.08 Ma consistent with its late Pliocene stratigraphy while coexisting shark teeth are variably reset by late-diagenesis. U–Pb dating on a paleosol sample from the Katberg Formation, Karoo Basin, South Africa yielded an age of 252 ± 3 Ma, which overlaps with a previous high-precision U–Pb zircon date from a volcanic ash deposit 2 meters above the paleosol demonstrating, for the first time, the reliability of using LA–ICPMS dating on terrestrial pedogenic calcite. Processing LA–ICPMS data at the single cycle level allows more precise absolute dating of fossils and carbonates. In some cases, separate regression of totally reset and partially reset domains can resolve ages of early and late diagenesis. Apatite fossils such as teeth or bones contain high U content, but they are more susceptible to late diagenetic alteration whereas calcitic invertebrate fossils like belemnites or rugose corals seem to be more stable but usually show low U content. Our research has demonstrated that pedogenic carbonate nodules and fossils can potentially be dated with meaningful precision, providing another mechanism to constrain the age of sedimentary sequences and study events associated with fossil extinctions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".