{"id":"W1964918537","doi":"10.1109/tac.2007.899024","title":"Curve Shortening and the Rendezvous Problem for Mobile Autonomous Robots","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polygon (computer graphics); Point in polygon; Mathematics; Regular polygon; Rendezvous; Mobile robot; Curvature; Convex polygon; Robot; Mathematical analysis; Geometry; Topology (electrical circuits); Computer science; Combinatorics; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001455135,0.0001652154,0.0002605913,0.0001503316,0.0004329581,0.0002214625,0.0003735525,0.00006962606,0.00002611488],"category_scores_gemma":[0.00001221672,0.0001174381,0.0001235125,0.0002633761,0.0001145361,0.0002614757,0.000002695193,0.0001533574,0.00001248244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005324738,"about_ca_system_score_gemma":0.00007660131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001977792,"about_ca_topic_score_gemma":0.00005253078,"domain_scores_codex":[0.9985326,0.0001088039,0.0004126793,0.0003163919,0.0002481219,0.0003813942],"domain_scores_gemma":[0.9982483,0.001029276,0.0001034653,0.0003880665,0.0001081379,0.0001226967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009650284,0.0001856677,0.000004030344,0.00005351658,0.0001327716,0.00000486204,0.002406533,0.2107467,0.0002132681,0.00739775,0.0001357904,0.7786226],"study_design_scores_gemma":[0.003941656,0.0001980173,0.00003189486,0.00002466431,0.00003314989,0.00002576436,0.00005984399,0.9936988,0.000310578,0.001096629,0.000433685,0.0001452937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004294767,0.00006228469,0.9950627,0.001220523,0.0002532645,0.002072999,0.000006951522,0.0004020005,0.0004897895],"genre_scores_gemma":[0.9044769,0.00001334041,0.09364926,0.0005413753,0.00002233456,0.0006552,6.761292e-7,0.00001655515,0.0006243136],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9040475,"threshold_uncertainty_score":0.4788985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309536530966073,"score_gpt":0.2599077172297869,"score_spread":0.2468123519201262,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}