Estimating Volumes of Coastal Shell Midden Sites Using Geometric Solids
Bibliographic record
Abstract
Abstract Coastal shell midden deposits are a quintessential component of the archaeological record on the Pacific Northwest Coast. Despite their importance in informing the cultural and environmental histories of Indigenous peoples, research on shell middens has largely not sought to address the physical extent of these cultural deposits, which requires estimating shape, depth, and volume. Here, we present a new scalable geospatial model, designed to work with legacy survey data, for estimating midden volumes based on applying a regular geometric solid to sites with known extent and depth. We evaluate the accuracy of this technique using percussion core, total station, and lidar data from eight sites in Tseshaht territory on western Vancouver Island and three sites on the north coast of British Columbia (Canada). As part of the evaluation process of our results, we calculate uncertainty using subsurface core depth data and then compare generalized and modeled midden volume estimates. We demonstrate an accurate general model applied at the regional scale across a systematically surveyed landscape. This work presents the first landscape-scale measure of midden extents and volume within our study area, with relevance to historical ecology and settlement 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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".