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Record W1994084567 · doi:10.3138/carto.43.2.85

Keyhole, Google Earth, and 3D Worlds: An Interview with Avi Bar-Zeev

2008· article· en· W1994084567 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.

venuePublished in a venue whose home country is Canada.
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

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2008
Typearticle
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsVisual artsEntertainmentMAGIC (telescope)Computer graphics (images)Rendering (computer graphics)World Wide WebArtComputer scienceMedia studiesSociology

Abstract

fetched live from OpenAlex

Avi Bar-Zeev is a co-founder of Keyhole () – maker of EarthViewer, which later became Google Earth ( http://earth.google.com ) – and an early employee of Intrinsic Graphics and a number of interesting start-ups. He developed technologies for Second Life, including the procedural 3D object rendering code. Early in his career, he helped develop Disney's Aladdin's Magic Carpet VR Ride, ( http://www.imagineering.org/wdilabs.html ), one of the first real-time (60 fps) first-person immersive entertainment applications, and went on to lead or influence a number of Disney 3D experiences. He typically consults for a living, inventing technologies as needed and helping clients through the maze of options. He regularly blogs about subjects related to his technical interests and expertise at http://www.realityprime.com .

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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