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Record W2557754993 · doi:10.1002/gea.21595

Micromorphological Analyses of Inuit Communal Sod Houses in Northern Labrador, Canada

2016· article· en· W2557754993 on OpenAlexafffundabout
Andréanne Couture, Najat Bhiry, James Woollett

Bibliographic record

VenueGeoarchaeology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsTramplingBayDetritusArchaeologyGeographyPhysical geographyGeologyEcologyPaleontology

Abstract

fetched live from OpenAlex

As part of ongoing multidisciplinary research at Uivak Point (HjCl‐09) and Oakes Bay 1 (HeCg‐8) in Labrador, Canada, undisturbed soil samples were collected in order to document archaeological sediments and examine anthropogenic processes within Inuit sod houses through soil micromorphology. These structures consist of multifamily winter dwellings used in Labrador and Greenland, which have been variously associated with Inuit social changes following contact with Europeans and environmental conditions prevailing during the “Little Ice Age.” Analyses of thin sections revealed anthropogenic features that can be associated with specific activities that are also documented independently through archaeological, anthropological, and historical sources. While sleeping platforms were characterized by low frequencies of wood and burnt organic matter, adjacent floor areas had moderate accumulations of a variety of anthropogenic features. The entrance tunnel area collected dense deposits of various kinds of detritus that showed evidence of trampling. Nevertheless, dedicated activity areas could not be documented with precision because of the small number of samples and the unexpected impact of household cleaning events.

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 score0.027
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.225
Teacher spread0.203 · 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
Published2016
Admission routes3
Has abstractyes

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