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Record W2170377350 · doi:10.1109/mcg.2002.1046632

Unwrapping and visualizing cuneiform tablets

2002· article· en· W2170377350 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Computer Graphics and Applications · 2002
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsnot available
FundersNational Research Council CanadaDirectorate for Computer and Information Science and Engineering
KeywordsInscribed figureComputer scienceComputer graphics (images)VisualizationRendering (computer graphics)CuneiformArtificial intelligenceComputer visionEngineering drawingGeometryMathematicsEngineering

Abstract

fetched live from OpenAlex

Cuneiform inscriptions, which scholars consider the first written language, were made in moist, clay tablets. We've developed a semiautomatic method for concisely displaying the tablets' inscribed writing, thereby providing a clear visualization that can be printed on paper. We first scan the tablets with 3D range scanners and use the scan data to construct a high-resolution 3D model (at a resolution of 50 microns). Next, we unwrap and warp the tablet surface to form a set of flat rectangles, one per side or edge of the tablet. This process permits all the writing to be seen at once, although necessarily slightly distorted. Finally, we apply curvature coloring and accessibility coloring to the unwrapped text, thereby replacing raking illumination with a nonphotorealistic rendering technique.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.028
GPT teacher head0.271
Teacher spread0.242 · 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