MétaCan
Menu
Back to cohort
Record W2963281409 · doi:10.1109/icca.2011.6138087

Optimal sensor configurations for rectangular target detection

2011· article· en· W2963281409 on OpenAlexafffund
François-Alex Bourque, Bao Nguyen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsDefence Research and Development Canada
FundersDefence Research and Development Canada
KeywordsOrientation (vector space)Symmetry (geometry)Computer scienceFeature (linguistics)Mathematical optimizationAlgorithmMathematicsArtificial intelligenceGeometry

Abstract

fetched live from OpenAlex

Optimal search strategies where targets are observed at several different angles are found. Targets are assumed to exhibit rectangular symmetry and have a uniformly-distributed orientation. By rectangular symmetry, it is meant that one side of a target is the mirror image of its opposite side. Finding an optimal solution is generally a hard problem. Fortunately, symmetry principles allow analytical and intuitive solutions to be found. One such optimal search strategy consists of choosing n angles evenly separated on the half-circle and leads to a lower bound of the probability of not detecting targets. As no prior knowledge of the target orientation is required, such search strategies are also robust, a desirable feature in search and detection missions.

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.

How this classification was reachedexpand

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: Methods · Consensus signal: Methods
Teacher disagreement score0.876
Threshold uncertainty score0.280

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 science0.0000.000
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 head0.044
GPT teacher head0.257
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2011
Admission routes2
Has abstractyes

Explore more

Same topicOptimization and Search ProblemsFrench-language works237,207