{"id":"W3026304322","doi":"10.48550/arxiv.1508.07603","title":"Line-of-Sight Pursuit in Monotone and Scallop Polygons","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Guidance and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Science Foundation","keywords":"Monotone polygon; Polygon (computer graphics); Pursuit-evasion; Combinatorics; Pursuer; Regular polygon; Line segment; Line (geometry); Point (geometry); Mathematics; Position (finance); Scallop; Line-of-sight; Boundary (topology); Computer science; Geometry; Mathematical optimization; Physics; Mathematical analysis; Frame (networking)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004584354,0.0008628231,0.0007147551,0.0004466929,0.0006773601,0.001553052,0.001309869,0.001108142,0.003354005],"category_scores_gemma":[0.003631355,0.0004188248,0.0007856812,0.0004511145,0.001739434,0.001951294,0.001784382,0.0009679585,0.0004355708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150385,"about_ca_system_score_gemma":0.0004393412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005227629,"about_ca_topic_score_gemma":0.002917772,"domain_scores_codex":[0.9994186,0.0001678857,0.00001940131,0.0001022003,0.0001216085,0.0001702414],"domain_scores_gemma":[0.9986219,0.0008274519,0.0002161135,0.00008592712,0.00005928047,0.0001893647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000505831,0.0001144878,0.004661641,0.0001472899,0.00005888768,0.001537055,0.0004667962,0.7635415,0.003146195,0.2099909,0.002001669,0.01382762],"study_design_scores_gemma":[0.00005278239,0.00009879931,0.0004465737,0.00002073839,0.00001861848,0.0002200141,0.0002285083,0.9411149,0.0006886173,0.05483212,0.00226475,0.00001346737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5247815,0.0005554002,0.4380478,0.0005956374,0.00007682169,0.0001524072,0.0003714409,0.000306352,0.03511252],"genre_scores_gemma":[0.9507404,0.0003737287,0.04118575,0.00006007072,0.00002431868,0.0000779068,0.0002426416,0.00008298215,0.007212063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005227629,"threshold_uncertainty_score":0.01122028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05622703341316117,"score_gpt":0.1676655183369689,"score_spread":0.1114384849238077,"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."}}