MétaCan
Menu
Back to cohort

Fast Ray-Axis Aligned Bounding Box Overlap Tests with Plucker Coordinates

2004· article· en· W2083340588 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Graphics Tools · 2004
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMinimum bounding boxSilhouetteIntersection (aeronautics)Vectorization (mathematics)Projection (relational algebra)Computer scienceAlgorithmDivision (mathematics)Bounding overwatchProduct (mathematics)Plane (geometry)Computer visionMathematicsArtificial intelligenceGeometryArithmeticImage (mathematics)Parallel computingEngineering

Abstract

fetched live from OpenAlex

Fast ray-axis aligned bounding box overlap tests can be performed by utilizing Pliicker coordinates. This method tests the ray against the edges comprising the silhouette of the box instead of testing against individual faces. Projection of the edges onto a two-dimensional plane to generate the silhouette is not necessary, which simplifies the technique. The method is division-free and successive calculations are independent and consist simply of dot product operations, which permits vectorization. The method does not compute an intersection distance along the ray to the box, but this can be added as an additional step. Storage of Pliicker coordinates is unnecessary, permitting integration into existing systems. Test results show the technique's performance is up to 93% faster than traditional methods if an intersection distance is not needed.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.463
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.030
GPT teacher head0.264
Teacher spread0.235 · 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