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Record W4281479282 · doi:10.1017/aap.2022.9

Estimating Volumes of Coastal Shell Midden Sites Using Geometric Solids

2022· article· en· W4281479282 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAdvances in Archaeological Practice · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsRaincoast Conservation FoundationTula FoundationUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of CanadaHakai InstituteNatural Sciences and Engineering Research Council of CanadaMitacsParks CanadaUniversity of Victoria
KeywordsMiddenArchaeologyGeographyScale (ratio)Settlement (finance)GeologyGeospatial analysisPhysical geographyRemote sensingCartography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.311
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it