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Record W1996691104 · doi:10.1002/gea.20106

Late Wisconsinan Port Eliza Cave deposits and their implications for human coastal migration, Vancouver Island, Canada

2006· article· en· W1996691104 on OpenAlexaffabout
M. Al‐Suwaidi, Brent Ward, M.C. Wilson, Richard J. Hebda, David W. Nagorsen, Daniel D. Marshall, Bassam Ghaleb, Rebecca J. Wigen, Randolph J. Enkin

Bibliographic record

VenueGeoarchaeology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of CanadaUniversité du Québec à MontréalRoyal British Columbia MuseumDouglas CollegeUniversity of VictoriaSimon Fraser University
Fundersnot available
KeywordsGeologyRadiocarbon datingGlacial periodCavePaleontologySiltArchaeologyColluviumPhysical geographyGeography

Abstract

fetched live from OpenAlex

Abstract Sediments of Port Eliza Cave provide a record of the Last Glacial Maximum (LGM) on Vancouver Island that has important implications for human migration along the debated coastal migration route. Lithofacies changes from nonglacial diamict to glacial laminated silt and clay and till, then a return to nonglacial conditions with oxidized clay, colluvial block beds, and speleothems, along with radiocarbon and U/Th dates, define glacial–nonglacial transitions. Scanning electron microscope studies and clay mineralogy confirm that the laminated fines represent glaciation. Preglacial faunal evidence shows a diverse range from small species, including birds, fish, vole, and marmot, to larger species, such as mountain goat. Pollen data from the same unit show a cold, dry tundra environment with sparse trees. Deglaciation occurred prior to an age of 12.3 ka B.P. based on dated mountain goat bone. These data support the viability of the coastal migration route for humans prior to ˜16 ka B.P. and then as early as ˜13 ka B.P. © 2006 Wiley Periodicals, Inc.

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)0.001
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 score0.021
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.221
Teacher spread0.211 · 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

Citations47
Published2006
Admission routes2
Has abstractyes

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