Compară metode

	Radiocarbon Calibration	Bayesian Chronological Modeling
Domeniu	Arheologie	Arheologie
Familie	Process / pipeline	Regression model
Anul apariției	2020	2009
Autorul original	Hans Suess (first curves); IntCal Working Group (P. J. Reimer et al.)	Christopher Bronk Ramsey (OxCal); Caitlin Buck and colleagues (Bayesian framework)
Tip	Probabilistic conversion of radiocarbon ages to calendar ages	Bayesian statistical model combining dates with prior archaeological information
Sursa seminală	Reimer, P. J., et al. (2020). The IntCal20 Northern Hemisphere Radiocarbon Age Calibration Curve (0-55 cal kBP). Radiocarbon, 62(4), 725-757.	Bronk Ramsey, C. (2009). Bayesian Analysis of Radiocarbon Dates. Radiocarbon, 51(1), 337-360.
Denumiri alternative	14C Calibration, IntCal Calibration, Calendar Calibration of Radiocarbon Dates	Bayesian Radiocarbon Modeling, OxCal Bayesian Chronology, Bayesian Phase Modeling, Chronological Bayesian Modeling
Înrudite	3	3
Rezumat	Radiocarbon calibration converts a laboratory radiocarbon measurement into a probability distribution over actual calendar years. It is necessary because the assumptions behind a raw radiocarbon age are not exactly true: the concentration of carbon-14 in the atmosphere has varied over time, so a measured radiocarbon age does not equal a calendar age. Calibration corrects for this by comparing the measurement against an internationally agreed curve — currently IntCal20 — that records the relationship between radiocarbon age and calendar age, reconstructed from precisely dated tree rings, corals, speleothems, and other archives. Because the curve wiggles, calibration typically yields an irregular, sometimes multi-peaked range of calendar years rather than a single date, and that range is the proper expression of a radiocarbon result.	Bayesian chronological modeling refines archaeological chronologies by combining the calibrated probability distributions of individual radiocarbon dates with prior archaeological knowledge — most importantly the stratigraphic order of samples and their grouping into phases — within a single Bayesian model. Rather than treating each date in isolation, the method asks what calendar ages are jointly consistent with all the dates and all the ordering constraints at once, and returns sharpened posterior distributions for each date plus estimates of the start, end, and duration of phases and the timing of events. Formalized by Caitlin Buck and colleagues and made widely usable through Christopher Bronk Ramsey's OxCal software, with the international IntCal calibration curve as input, it has become the standard framework for high-precision archaeological dating.