Estimation of the ages of Devonian and Cretaceous stage boundaries in the Geologic Time Scale
Bibliographic record
Abstract
Estimation of the ages of period and stage boundaries of the Geologic Time Scale (GTS) has a long history that commenced over a century ago with the pioneering work of Arthur Holmes. Frequencies, precision and accuracy of radiogenic isotope age determinations used for time scale construction continue to increase steadily. Later stage boundary age estimates are accompanied by error bars based on 2-sigma age dating errors with incorporation of stratigraphic uncertainty. Most GTS2004 and GTS2012 results involved spline-curve fitting. In GTS2012, Milankovitch-type orbital climate cyclicity was used to tune the Neogene geologic time scale while seafloor spreading was combined with sedimentary cycle scaling to construct the Paleogene time scale, and it also contributed to the construction of the Cretaceous and Jurassic time scales. Geomathematical procedures continue to be refined for the next GTS which is in Gradstein et al. (2020). In this study smoothing splines are used to construct Devonian and Late Jurassic - Early Cretaceous time scales. This methodology and its results are described and some estimates are refined by incorporating Milankovitch cycle durations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".