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Record W2005378658 · doi:10.1179/009346907791071467

The Changing Pre-Dorset Landscape of SW Hudson Bay, Canada

2007· article· en· W2005378658 on OpenAlexaboutno aff
Lisa Hodgetts

Bibliographic record

VenueJournal of Field Archaeology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsArchaeologyRadiocarbon datingBaySubarctic climateExcavationPeriod (music)GeographyRange (aeronautics)Peninsula

Abstract

fetched live from OpenAlex

The Pre-Dorset peoples were mobile hunter-gatherers who rapidly colonized the eastern Canadian Subarctic around 4000 B.P. (uncalibrated radiocarbon years) and continued to occupy the region until about 2700 B.P. In 2005, the Churchill Archaeological Project undertook excavations at two Pre-Dorset sites in sw Hudson Bay (northern Manitoba, Canada) near the southernmost extent of the Pre-Dorset range. The goal of the fieldwork was to examine the relationship between changes in the physical landscape and the social landscape of the region over the course of the Pre-Dorset period. It demonstrated that Pre- Dorset groups entered the area at least 700 radiocarbon years earlier than previously documented and illustrated marked differences in lithic technology between the early and late Pre-Dorset occupations. While the results suggest that the area may have been abandoned during the middle part of the Pre-Dorset period, further work is required in order to determine whether the region is a typical “peripheral” area as outlined in the “core area” hypothesis.

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 score0.022
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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