Radiocarbon dating marine shell: challenges and opportunities in Canadian coastal archaeology
Bibliographic record
Abstract
Marine mollusk shells are the most abundant materials found at coastal archaeology sites. They are often found in large accumulations called middens which are formed as a result of shellfish processing activities and may be features of dwelling sites. Despite the abundance of marine mollusk shells at coastal sites, terrestrial samples are often favoured for radiocarbon analysis because they are free from local marine reservoir effects. In this thesis, I investigate intra-shell radiocarbon variability in three mollusk species from coastal sites across Canada: Saxidomus gigantea from British Columbia, Mya arenaria from Nova Scotia, and Crassostrea virginica from Prince Edward Island. Each of these species has different growth strategies that must be considered to understand time-averaging effects in the radiocarbon measurements. Short-lived C. virginica samples from Prince Edward Island had the best agreement between intra-shell radiocarbon measurements. Additional radiocarbon measurements on twelve M. arenaria shells from Port Joli Harbour, Nova Scotia show good agreement with the previously published terrestrial dates and paired marine-terrestrial samples are used to calculate the first archaeological ΔR values for the region. Building confidence in marine shell radiocarbon will greatly widen the number of samples that archaeologists can study from coastal midden sites, especially ones that may be rapidly eroding and lack terrestrial samples.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".