LOCAL MARINE RESERVOIR AGE (ΔR) RECONSTRUCTED BASED ON THE TSUNAMI DEPOSIT FROM PANGANI BAY (TANZANIA)
Bibliographic record
Abstract
ABSTRACT Quantifying the local marine reservoir age (ΔR) and its change over time is critical for precise radiocarbon calibration of marine samples and for the study of the ocean carbon cycle. ΔR values are scarce for the African coast facing the Indian Ocean, and the few values available were obtained from pre-bomb shells collected during the 19th century. Here, the ΔR value for calibrated year 1110 ± 25 (1σ) CE was reconstructed from radiocarbon dating and Bayesian analysis of marine and terrestrial materials coexisting in a tsunami deposit discovered in Pangani Bay (Tanzania, western Indian Ocean coast). The reconstructed ΔR of –8 ± 40 (1σ, n = 3) is similar to pre-bomb regional estimates and provides new information to investigate regional ΔR change over time. The Bayesian analysis of the dated samples revises the age of the tsunami event found in Pangani Bay to 1064–1157 cal CE (95.4% confidence level) or 1110 ± 25 (1σ) cal CE, about one century younger compared to the previous estimate. Our results indicate that the new ΔR value and the proposed calibration approach can be used to refine existing chronologies in the region, with implications for paleo-environmental reconstructions and archaeological studies of Early Swahili societies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".