{"id":"W2119288811","doi":"","title":"The Gaussian Centre of a Set of Mobile Points","year":2003,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Facility location problem; Position (finance); Bounded function; Euclidean geometry; Set (abstract data type); Computer science; Motion (physics); Function (biology); Gaussian; Mathematical optimization; Mathematics; Mathematical analysis; Geometry; Physics; 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":[0.001726419,0.0009178284,0.001306634,0.001724463,0.0007517067,0.002112722,0.003030367,0.002337591,0.003802127],"category_scores_gemma":[0.01200747,0.0007149677,0.00136226,0.001926652,0.002180231,0.002633651,0.00384279,0.001719872,0.002395443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590487,"about_ca_system_score_gemma":0.002048898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01050129,"about_ca_topic_score_gemma":0.006275321,"domain_scores_codex":[0.9983359,0.0003525094,0.00008060088,0.000369109,0.0006366631,0.0002252173],"domain_scores_gemma":[0.9967299,0.001036161,0.0003402675,0.0006661364,0.0009465374,0.0002810005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006788472,0.00008058841,0.004514776,0.0003216235,0.00009120176,0.0005125877,0.0004255491,0.6584504,0.01019813,0.210804,0.01159699,0.1023253],"study_design_scores_gemma":[0.00003268647,0.00007683325,0.0004441451,0.00003246379,0.00001700831,0.0001822514,0.00005244357,0.9594291,0.002576857,0.03009119,0.007029082,0.00003587789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01246058,0.0002677549,0.9840955,0.0001753379,0.00006887463,0.00004933414,0.0002252619,0.0006001858,0.002057201],"genre_scores_gemma":[0.4631685,0.001156849,0.52335,0.0003744765,0.0002348643,0.0003623526,0.001402702,0.0004071026,0.009543156],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01050129,"threshold_uncertainty_score":0.02088034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064034594157075,"score_gpt":0.2478583186047206,"score_spread":0.2272179726631499,"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."}}