11,500 y of human–clam relationships provide long-term context for intertidal management in the Salish Sea, British Columbia
Bibliographic record
Abstract
) throughout the Holocene in the northern Salish Sea of British Columbia, Canada. We compare butter clam size and growth patterns from different temporal, environmental, and cultural contexts spanning 11,500 y to present. Butter clam size and growth were restricted in early postglacial times but increased over the next few millennia. During the early-Late Holocene, humans took increasing advantage of robust clam populations and after 3.5 ka, began constructing clam gardens (intertidal rock-walled terraces). Environmental and cultural variables, including coarse substrate, stabilized sea surface temperature, and the presence of a clam garden wall, increased clam growth throughout the Holocene. Measurements of clams collected in active clam gardens and deposited in middens suggest that clam gardens as well as other mariculture activities enhanced clam production despite increased harvesting pressure. Since European contact, decline of traditional management practices and increases in industrial activities are associated with reduced clam size and growth similar to those of the early postglacial clams. Deeper-time baselines that more accurately represent clam population variability and allow us to assess magnitudes of change throughout time as well as the complex interactions among humans and clams are useful for modern marine resource management.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".