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Record W2084399632 · doi:10.1179/009346905791072134

A Three-Dimensional Model of a Thule Inuit Whale Bone House

2005· article· en· W2084399632 on OpenAlexaboutno aff
Peter Dawson, Richard Levy

Bibliographic record

VenueJournal of Field Archaeology · 2005
Typearticle
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsWhaleArcticArchaeologyBaleenPrehistoryThe arcticGeologyGeographyComputer scienceOceanographyEcologyBiology

Abstract

fetched live from OpenAlex

The semi-subterranean whale bone house is one of the most distinctive features of Thule Inuit culture in the Canadian Arctic (A.D. 1000–1600). An understanding of how these remarkable dwellings were designed and built has been hindered by measurement and recording techniques restricted to two dimensions. Determining how the unusual shapes and sizes of whale bone elements would have influenced the strength of the roof frame and the volume of the house's interior requires a three-dimensional point of view. We constructed a three-dimensional computer model of such a house by first employing laser scanning technology to create a digital model of a North Atlantic Right Whale skeleton on display at the New England Aquarium in Boston, Massachusetts. Individual elements from the digital model were used in combination with archaeological data to construct an accurate representation of a Thule whale bone dwelling. Constructing a model in a virtual world is analogous to building one in the real world. Consequently, we gained a deeper understanding of the design principles used by Thule builders, and conclude that the development of an architectural tradition based upon whale bone may be among the greatest technological achievements in Arctic prehistory.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.235
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations13
Published2005
Admission routes1
Has abstractyes

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