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Record W1480970423

From Laser Scanning to Virtual Reality: The Art and Science of Constructing a Thule Whalebone House

2005· article· en· W1480970423 on OpenAlexaffabout
Richard Levy, Peter Dawson

Bibliographic record

VenueEdMedia: World Conference on Educational Media and Technology · 2005
Typearticle
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsArcticArchaeologyThe arcticSnowVirtual realityGeographyPhysical geographyGeologyComputer scienceMeteorologyOceanographyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This paper will also focus on opportunities to use virtual reality (VR) technology as a laboratory for testing and presenting research alternatives in archaeology to college students and the public. During the last decade the development of laser scanning technology has created a new technique for capturing, preserving and analyzing objects, artifacts and sites. Using the reconstruction of a Thule whalebone house, issues of data translation, computer modeling and virtual world construction are considered. Finally, the advantages of advantages of different platforms for presenting 3D content as interactive worlds are also explored. Reconstruction of a Thule Whalebone House The reconstruction of a Thule whalebone house provides a good case study of the use of laser scanning on an object of complex geometry. Thule peoples are the cultural and biological ancestors of contemporary Inuit and Eskimo groups of the North American Arctic and Greenland. By the late 12 or early 13 century, Thule groups had expanded eastward from the Bering Strait region into the Canadian Arctic. Unlike northwestern Alaska, the coastlines of the Eastern Arctic were largely devoid of driftwood. Consequently, the main rooms, kitchen areas, and entrance tunnels of Thule winter houses were constructed from whalebone, which was used extensively within the roof framework. This roof framework was erected over a house pit furnished with a flagstone floor, raised sleeping platform, kitchen, and storage areas. The roof frame would have then been covered with hide and a thick layer of turf, moss and snow (Maxwell 1985:248; McGhee 1978:92,95). Archaeologists know little about how these enigmatic houses were constructed because few have ever been encountered intact. Consequently the possibility of reconstructing a three dimensional model of a Thule house from archaeological data held great promise for providing new insights into how these dwellings were constructed and used. The reconstruction process would have been difficult, if not impossible, to resolve using 2D drawings since manual drafting or 2D CAD cannot easily solve a 3D structural system based on the organic elements, such as the mandibles, cranium and maxillas of a whale. Physical models, however, offer an interesting environment for manually testing possible solutions, avoiding the need to create curvilinear forms from 2D drawings. Tracing the modeling process also provides an opportunity to address issues of workflow, revealing the limitations of commercially available software and hardware in data translation. Furthermore, we illustrate the testing of research hypotheses and include a review of the types of products created during the

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.267
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2005
Admission routes2
Has abstractyes

Explore more

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