Measurements of the Marine Reservoir Effect on Radiocarbon Ages in the Eastern Bering Sea
Bibliographic record
Abstract
The marine reservoir effect is known to skew radiocarbon dating (marine samples appear "older" than terrestrial samples of equivalent age), but the magnitude of this effect is not the same in all locations. Carbon-14 age determinations from 23 paired samples of terrestrial and marine origin are presented for five areas around the northern and eastern Bering Sea. It appears statistically suitable to average the age differences for three pairs, weighted inversely by variance. Differences from within each of 14 pairs of wood charcoal vs. sea mammal residue (from St. Lawrence Island, Cape Prince of Wales, Nunivak Island, Alaska Peninsula, and Unalaska Island) yield a weighted mean of 737 ± 20 years. Somewhat more variant differences from within each of five additional pairs of wood charcoal vs. sea mammal residue (St. Lawrence Island, Unalaska Island) provide a lower weighted mean of 460 ± 41 years. Differences from within each of four pairs of wood charcoal vs. marine shell (Nunivak Island) produce a weighted mean of 459 ± 32 years. Variations in these apparent reservoir effects presumably result largely from the interplay of differential ocean water upwelling and customary faunal feeding areas, although possible effects of other species characteristics cannot be ruled out. Dating of marine samples from the Bering Sea should thus either proceed with the expectation that age determinations may not be accurate within several centuries, or be approached through experimental measurement of reservoir effect among restricted faunal species in limited areas. Overall, the effect throughout the eastern Bering Sea appears to range from about 450 to 750 years.
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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 | 0.001 | 0.000 |
| 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".