Evaluating Quoddy Region archaeological site vulnerability to sea-level rise and erosion through the integration of geographic information system modeling and surveys
Bibliographic record
Abstract
Modeling archaeological site erosion often depends on regional site databases that record sites accurately but with variable precision. This study examines the impact of sea-level rise (SLR) on 10 archaeological sites in the Quoddy Region of Maine through comparing models and field observations. Sites were categorized as low, mid, or high priority for field excavation based on exposure to tides. These model results were compared to field reports of site condition to evaluate the accuracy of modeling SLR as an indicator of erosion and to evaluate the application of models in developing prioritization protocols for site investigations. Models for current sea level scenarios broadly underestimate the degree of erosion reported by field observations because not all site locations were recorded at the precision required for analysis. This study emphasizes the importance of field audits for sites recorded in databases to enable large-scale modeling for the prioritization of urgently threatened sites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".