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Record W2070549473 · doi:10.1080/00438243.2014.890911

Sustainable archaeology through progressive assembly 3D digitization

2014· article· en· W2070549473 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWorld Archaeology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsDigitizationLibrary scienceArchaeologyTourismResource (disambiguation)InternshipSociologyHistoryEngineeringComputer sciencePolitical science

Abstract

fetched live from OpenAlex

AbstractThree-dimensional object scanning for both diagnostic and collection management has become more accepted within archaeological research over the last few years. However, the ability to scan vast numbers of cultural artefacts effectively has been stunted by the lack of technical expertise, cost of both hardware and software tools, and access to full collections. This article examines the issues related to mass scanning techniques and their potential effectiveness to enable research on and access to extensive archaeological collections. It attempts to lay the groundwork for sustainable and effective scanning methodologies within multiple contexts of practice, including cultural resource management and collections management facilities.Keywords: 3D scanningstructured light scanner3D visualizationcultural resource management AcknowledgementsSustainable Archaeology and Museum of Ontario Archaeology staff, particularly Christine Saly, Kira Westby, Dr Rhonda Bathurst and Zoe Morris, were a huge support to the project, as were Thomas Tong and Kai Wong at 3D3 Solutions.FundingThis project was funded by the Canada Foundation for Innovation, Ontario Research Fund, Ontario Ministry of Culture, Sport and Recreation Museum Technology Fund, a graduate student Accelerate Internship program supported by MITACS, and a partnership with theskonkworks incorporated.Notes1 In a separate part of the SA facility are three 2D photography light-box stations where higher-resolution, 16-megapixel DSLRs generate high-quality images of all objects entering SA.Additional informationNotes on contributorsNamir AhmedNamir Ahmed, MA candidate, Western University, is the Sustainable Archaeology Animation Unit Project Coordinator.Michael CarterMichael Carter, PhD candidate, Western University, is the Program Coordinator – Digital Specialization Program, Digital Media Zone and Masters in Digital Media Program, Ryerson University.Neal FerrisNeal Ferris, Lawson Chair of Canadian Archaeology, Western University and Museum of Ontario Archaeology, is the Principal Investigator for Sustainable Archaeology.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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