{"id":"W2952265578","doi":"10.48550/arxiv.1003.1423","title":"On Vehicle Placement to Intercept Moving Targets","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Army Research Office; Office of Naval Research; Multidisciplinary University Research Initiative; Institute for Collaborative Biotechnologies; Deutscher Akademischer Austauschdienst","keywords":"Line (geometry); Function (biology); Line segment; Regular polygon; Perpendicular; Computer science; Mathematical optimization; Control theory (sociology); Mathematics; Algorithm; Geometry; Artificial intelligence","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":[0.001081641,0.001508335,0.001334524,0.001017652,0.001042373,0.000938003,0.001315877,0.001898055,0.002124416],"category_scores_gemma":[0.005111352,0.0008323574,0.0006032599,0.0009504727,0.002116875,0.001483369,0.001577267,0.001256587,0.000473864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002101443,"about_ca_system_score_gemma":0.001481909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009464188,"about_ca_topic_score_gemma":0.004266636,"domain_scores_codex":[0.9994127,0.0002178247,0.00002004383,0.0001247582,0.0001006394,0.0001240851],"domain_scores_gemma":[0.9977519,0.001367496,0.0003233733,0.00012257,0.0002641985,0.000170468],"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":[0.00005007906,0.00002696466,0.0002294725,0.00003322076,0.00001211872,0.00003232453,0.00005228347,0.983216,0.0009600614,0.009513002,0.0003217213,0.005552771],"study_design_scores_gemma":[0.00002289922,0.00006377101,0.0000947919,0.000007812557,0.000005245138,0.00001636236,0.00002935452,0.9887643,0.0007242181,0.009811874,0.0004508536,0.000008584827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03692963,0.000316898,0.9593129,0.0002982546,0.00004092486,0.0001289414,0.00005227948,0.0001763783,0.002743821],"genre_scores_gemma":[0.7398385,0.0006640428,0.2539274,0.0001236152,0.00006824439,0.0003510953,0.0001642831,0.0001516773,0.00471116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009464188,"threshold_uncertainty_score":0.0188182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04484304085510872,"score_gpt":0.1907701662243716,"score_spread":0.1459271253692629,"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."}}