{"id":"W2134408180","doi":"10.1142/s0218195905001786","title":"MAXIMIZING A VORONOI REGION: THE CONVEX CASE","year":2005,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Voronoi diagram; Power diagram; Mathematics; Centroidal Voronoi tessellation; Combinatorics; Plane (geometry); Regular polygon; Weighted Voronoi diagram; Position (finance); Point (geometry); Set (abstract data type); Geometry; Computer science","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":[0.0027793,0.001028291,0.002010545,0.0008470991,0.001187039,0.001992962,0.002795163,0.001629303,0.003503041],"category_scores_gemma":[0.02541135,0.001055393,0.0008839151,0.001424357,0.002776513,0.005989975,0.003156973,0.00147223,0.0005815324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037901,"about_ca_system_score_gemma":0.0005914854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001718978,"about_ca_topic_score_gemma":0.001485773,"domain_scores_codex":[0.9975241,0.0008930429,0.00007544541,0.0004592653,0.0007000152,0.0003481654],"domain_scores_gemma":[0.9890298,0.008198882,0.001088354,0.0006401188,0.0006001478,0.0004427339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003076958,0.0001029799,0.00304755,0.0003323562,0.0001022568,0.001498873,0.0009765651,0.4490988,0.007537894,0.4635041,0.003722706,0.06976827],"study_design_scores_gemma":[0.00004624476,0.00009791416,0.0008134252,0.00004419056,0.00003336513,0.0007876367,0.0002542298,0.772274,0.004612219,0.2176095,0.003391044,0.00003617608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06767101,0.0008182736,0.9152383,0.0006916299,0.00002035266,0.00008148187,0.0000901726,0.0001141812,0.01527476],"genre_scores_gemma":[0.8152984,0.001076423,0.1774863,0.0001319297,0.0001386314,0.0001886264,0.0001288087,0.0001651753,0.005385666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003503041,"threshold_uncertainty_score":0.01469857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837095015847291,"score_gpt":0.2848444143815391,"score_spread":0.2664734642230662,"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."}}