Rigorous Identification of Variations and Changepoints in the Observed Rates of Radiocarbon Samples Over Time 
Bibliographic record
Abstract
A commonly-used approach to estimate changes in the frequency of past events or the size of populations looks at variations in the rate of archaeological and environmental samples (e.g., charcoal from fires, human/animal bones, or other evidence of occupation) found at a site over time. Time periods with large numbers of samples suggest increased activity, while those with few samples indicate a reduced level of activity. Variations and abrupt changes in the rate of observed samples might suggest the influence of important external environmental factors. This paradigm is known as “dates-as-data”.The reliability of such a “dates-as-data” approach is highly dependent upon our ability to estimate the calendar ages of the discoveries. Most archaeological/environmental dates are obtained using radiocarbon (14C). All 14C determinations need to be calibrated in order that they can be understood on the calendar scale. This introduces considerable uncertainties in the resultant calendar ages and complicates the identification of changepoints in the calendar year rates at which samples occur.In this talk, we provide a statistically rigorous approach to overcome these challenges. We model the occurrence of events (each assumed to leave a 14C sample in the archaeological/environmental record) as an inhomogeneous Poisson process, estimating the varying rate of samples using reversible-jump Markov Chain Monte Carlo. Given a set of radiocarbon samples, we aim to reconstruct how their occurrence rate varies over calendar time and identify if there are statistically significant changepoints in the rate at which the samples arise (i.e., specific times at which the rate of events abruptly changes).We will demonstrate our approach on data exploring the expansion of humans, and the parallel disappearance of megafauna, in the Yukon and Alaska in the late Pleistocene and early Holocene: investigating both the timings of such migrations in comparison with the climatic changes known to have occurred during this period, and the potential interactions between humans and the various species in the region.
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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 | 0.026 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".