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Record W4387342368 · doi:10.1080/15564894.2023.2227135

“… the most delicious fish …”—toward a zooarchaeology of the green sea urchin, <i>Strongylocentrotus droebachiensis</i> , on the coastal Northeast of North America

2023· article· en· W4387342368 on OpenAlexafffund
A. Katherine Patton, Arthur Anderson, David W. Black

Bibliographic record

VenueThe Journal of Island and Coastal Archaeology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of New BrunswickUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaHarrison McCain FoundationUniversity of New BrunswickNational Geographic Society
KeywordsStrongylocentrotus droebachiensisSea urchinArchaeologyZooarchaeologyExtant taxonFisheryGeographyHistoryEcologyBiology

Abstract

fetched live from OpenAlex

Recent studies have underlined the importance of shellfish in Ancestral Wabanaki diets. Green sea urchin (Strongylocentrotus droebachiensis) remains are a substantial component of shellfish assemblages from some Ancestral Wabanaki habitation sites and are present in smaller amounts in many other archaeological sites on the coastal Northeast. We summarize extant knowledge of archaeological sea urchin remains in the Quoddy Region of New Brunswick and Maine, part of the traditional homeland of the Peskotomuhkatiyik (the Passamaquoddy people). We position this information in regional historical, ecological, and archaeological contexts. Our results suggest that sea urchins were harvested at specific points in the annual tidal cycle. We also suggest that changes in sea urchin abundance through time could reflect changes in local environments, perhaps partially associated with changing climates.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.270
Teacher spread0.255 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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