{"id":"W3138190323","doi":"10.1145/1882261.1866176","title":"Cone carving for surface reconstruction","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Point cloud; Carving; Visibility; Surface (topology); Computer science; Computer vision; Surface reconstruction; Cone (formal languages); Point (geometry); Artificial intelligence; Geometry; Position (finance); Mathematics; Topology (electrical circuits); Algorithm; Optics; Physics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001073755,0.0001051256,0.0001156173,0.0001254503,0.0001664828,0.00002647174,0.0001170582,0.0001183417,0.00004629987],"category_scores_gemma":[0.0000138249,0.0001128482,0.00014343,0.0002433923,0.00003271171,0.00008289143,7.155513e-7,0.0003306118,0.000008703862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009895081,"about_ca_system_score_gemma":0.000007400044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001932734,"about_ca_topic_score_gemma":0.0002564821,"domain_scores_codex":[0.9994863,0.000006028488,0.000143784,0.0001351661,0.00007739913,0.0001513421],"domain_scores_gemma":[0.9994529,0.0001017979,0.00001456779,0.0003187079,0.00005850877,0.00005344562],"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":[0.00001929608,0.00006974889,0.0002680617,0.00009956631,0.0003656927,9.929173e-7,0.0002670969,0.7377815,0.05859136,0.000606049,0.0002162275,0.2017144],"study_design_scores_gemma":[0.0005845868,0.00005223365,0.0001226279,0.00003735863,0.0002348512,0.00002352576,0.0001276546,0.9578357,0.03053956,0.008135759,0.001855285,0.0004508927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3792567,0.00002515732,0.6194507,0.0001529706,0.0006371871,0.00006306614,0.00002812606,0.0002525446,0.0001335985],"genre_scores_gemma":[0.9865091,0.0001200282,0.01317593,0.00003567122,0.00004485678,0.0000150539,0.000006285871,0.00002721787,0.00006585006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6072524,"threshold_uncertainty_score":0.4601817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01484575960257848,"score_gpt":0.2258429359896188,"score_spread":0.2109971763870404,"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."}}