Coastal landscapes & indigenous histories of shellfish harvesting in Atlantic Canada: Mya arenaria as a new proxy for shellfish harvesting pressure in Port Joli, Nova Scotia.
Bibliographic record
Abstract
Marine bivalves from archaeological shell middens sites reveal critical information about past \nenvironments, harvesting strategies, and human impacts on shellfish populations. However, robust \nsample sizes are required to develop meaningful interpretations over time and space. Port Joli, \nNova Scotia (NS), has the densest concentration of shell midden deposits in Atlantic Canada, \ndating to ~1600 cal BP. A protocol for rapid-age at-death assessments of Mya arenaria, was \ndeveloped by analysing live-collected M. arenaria to establish a baseline for interpreting \narchaeological shell growth patterns. Rapid-age-at-death assessments of M. arenaria reveal \ninsights for both sclerochronological methods and archaeological interpretation. One-hundred \narchaeological shells were selected from six shell middens to interpret regional trends in shellfish \nharvesting. Chondrophores were sectioned to 3mm, mounted on slides, polished, and imaged using \nreflected light at 20x. Each image was analysed by four independent observers to assess: 1) quality \nof growth lines; 2) shell portion with the clearest lines; 3) relative age; 4) ontogenetic age; 5) \nseason of death. Variation in growth patterns was observed between modern and archaeological \nspecimens, with modern shells having better clarity. Further variation was observed with \nreadability between archaeological sites and variation in the average age between sites, suggesting \nthat some clam beds were harvested more than others. The results also demonstrate the level of \nexperience in sclerochronology will produce more conservative age and seasonality estimates, and \nthat novice readers are more likely to miss-characterize growth patterns.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".