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Record W2566378232 · doi:10.1080/15564894.2016.1256357

Prehistoric Mountain Goat <i>(Oreamnos americanus)</i> Mother Lode Near Prince Rupert, British Columbia and Implications for the Manufacture of High-Status Ceremonial Goods

2016· article· en· W2566378232 on OpenAlexaboutno aff
Susan J. Crockford

Bibliographic record

VenueThe Journal of Island and Coastal Archaeology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPrehistoryArchaeologyGeographyBay

Abstract

fetched live from OpenAlex

Abundant mountain goat (Oreamnos americanus) remains were recovered from two archaeological sites on Kaien Island near Prince Rupert Harbour, British Columbia. No other archaeological sites in North America have anywhere near the abundance of mountain goat remains as were recovered from GbTo 54 (NISP 410, 7.1% of identified mammals) and GbTo 13 (NISP 27, 5.4% of identified mammals). In contrast, at the impressive Boardwalk site on nearby Digby Island (GbTo 31), only 1% of identified mammals were identified as mountain goat, although goat remains from Grassy Bay (GbTn 1), also on Kaien Island, comprised 1.7% of identified mammals. With one exception, other western North American sites, including those in Alaska, recovered only a few pieces of mountain goat each (<0.5% of identified mammals). The dates for GbTo 54 and GbTo 13 span AD 200–AD 1300, with all four directly dated goat bones falling within that period. Most goat bones appeared to come from adult or subadult males and element abundance analysis of GbTo 54 remains indicate that whole animals may have been selectively butchered into transportable units. Other evidence suggests the occupants may have specialized in the procurement of a variety of raw materials (not only mountain goat) used in the manufacture of high-status ceremonial goods.

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 score0.323
Threshold uncertainty score0.650

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 studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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