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Record W2101350081 · doi:10.1109/iros.2006.281873

Where to Build a Door

2006· article· en· W2101350081 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsSimon Fraser UniversityUniversity of Lethbridge
Fundersnot available
KeywordsPolygon (computer graphics)Visibility polygonBoundary (topology)Simple polygonVisibilityComputer sciencePoint (geometry)CombinatoricsAlgorithmComputer graphics (images)MathematicsMonotone polygonComputer networkGeometryPhysicsOptics

Abstract

fetched live from OpenAlex

A room is a simple polygon with a prespecified point, called the door, on its boundary. Search starts at the door, and must detect all intruders that may be in the room, while making sure that no intruder escapes through the door during the search. Depending on where the door is placed, the intruders may be able to avoid detection. We present an efficient algorithm that can determine all the intervals on the boundary where the door should be placed in order for the polygon to be searchable by two guards on the boundary who keep mutual visibility, or a single searcher with a flashlight. Our algorithm works in O(n log n) time, where n is the number of vertices of the given polygon

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.633
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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