{"id":"W4238138432","doi":"10.1145/1661412.1618522","title":"Consolidation of unorganized point clouds for surface reconstruction","year":2009,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Point cloud; Outlier; Computer science; Normal; Algorithm; Iterative closest point; Cloud computing; Iterative method; Surface (topology); Computer vision; Mathematical optimization; Artificial intelligence; Mathematics; Geometry","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":[0.00009265622,0.00004570586,0.0001001183,0.00002718847,0.0000153147,0.00000625138,0.00002648106,0.000032035,0.00006563952],"category_scores_gemma":[0.0000142959,0.00004359512,0.00004341646,0.00008734864,0.000005301064,0.00004412047,0.000001266465,0.00002278234,0.000004762214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001346989,"about_ca_system_score_gemma":0.000005322134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004948228,"about_ca_topic_score_gemma":0.000002265461,"domain_scores_codex":[0.9996986,0.000005138848,0.0001419542,0.00005573444,0.00003498559,0.00006353479],"domain_scores_gemma":[0.9998241,0.00001992213,0.00001725125,0.00007002545,0.00005225953,0.00001645848],"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":[0.00002143351,0.00002651542,0.0002431655,0.00005030142,0.00009951543,1.533578e-7,0.0002090429,0.6036445,0.3257203,0.001782646,0.00175521,0.06644725],"study_design_scores_gemma":[0.0002601873,0.00002112362,0.00005297501,0.000009610022,0.00002770982,0.000002068067,0.00007415059,0.8536647,0.1441149,0.001660532,0.00004123064,0.00007083148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5382721,0.00003453542,0.4593646,0.0001170752,0.00006459858,0.00004572986,0.000003076285,0.0001252764,0.001973059],"genre_scores_gemma":[0.9845039,0.00002233081,0.01529338,0.00001563112,0.00002091158,4.928036e-7,0.000008616431,0.000005507289,0.0001292845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4462318,"threshold_uncertainty_score":0.1777757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00975003650477991,"score_gpt":0.2155011106533065,"score_spread":0.2057510741485266,"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."}}