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Record W4404369343 · doi:10.70460/jpa.v13i1.341

Exploratory and integrative study of Māori kurī (Canis familiaris) at the NRD archaeological site in Aotearoa New Zealand

2022· article· en· W4404369343 on OpenAlexaff
Robyn Kramer, Karen Greig, Matthew Campbell, Patricia Pillay, Melinda S. Allen, Charlotte L. King, Hallie R. Buckley, Clément P. Bataille, Beatrice Hudson, Stuart Hawkins, David Barr, Malcolm Reid, Claudine Stirling, Elizabeth Matisoo‐Smith, Rebecca Kinaston

Bibliographic record

VenueJournal of Pacific Archaeology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAotearoaCanisArchaeologyExploratory researchGeographySociologyAnthropologyEthnologyHistoryEcologyGender studiesBiology

Abstract

fetched live from OpenAlex

This multidisciplinary study analyzes kurī skeletal remains from the Northern Runway Development (NRD) archaeological site (AD 1400-1800) to develop an “osteo-history” and help us better understand 1) human-dog interactions; 2) the role kurī played in early Māori societies; and 3) to potentially use kurī as a proxy for human behavior at the site. We combine dental analysis with stable isotope analyses of bone and tooth dentine to investigate the kurī diet. Additionally, we use strontium isotope and mitogenomic analyses to explore the migration histories of the kurī and, by proxy, the humans they lived among at the NRD site during the late pre-contact period in Aotearoa. Through our exploratory investigation of the kurī skeletal remains, we found evidence of extensive interaction spheres with nearby and potentially distant communities. Furthermore, the kurī were healthy, demonstrated minimal tooth wear, and they subsisted heavily on a protein-rich, marine diet. This study demonstrates that variability is present in the origins, diet, health, and treatment of kurī at a single locality. Because of this, we believe it is important to include kurī in future archaeological investigations in Aotearoa to help build our foundational understanding of variability across sites and regions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.238
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0010.002
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 head0.014
GPT teacher head0.232
Teacher spread0.217 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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