{"id":"W3214202416","doi":"10.3390/s21227630","title":"Multiple Cylinder Extraction from Organized Point Clouds","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Cylinder; Geometric primitive; Point cloud; Ellipsoid; Computer science; Computer vision; Point (geometry); Artificial intelligence; Feature extraction; Object detection; Detector; Algorithm; Extraction (chemistry); Mathematics; Pattern recognition (psychology); Geometry; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000276532,0.001272479,0.001090147,0.003944481,0.000490421,0.001014652,0.001066488,0.0006385889,0.0009676997],"category_scores_gemma":[0.001077448,0.0005942655,0.0008999784,0.002916223,0.0003371281,0.001168149,0.001419365,0.0005629939,0.0009737803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004748264,"about_ca_system_score_gemma":0.001081624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006392717,"about_ca_topic_score_gemma":0.01078998,"domain_scores_codex":[0.9992815,0.00004087852,0.00002456614,0.000108441,0.0004435119,0.0001012516],"domain_scores_gemma":[0.9994517,0.00007637824,0.00007056633,0.00008723376,0.000278888,0.00003523742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003823438,0.00009360377,0.006232722,0.0003727541,0.0001392664,0.0009456942,0.0003041823,0.1255287,0.1816328,0.006166392,0.00591195,0.6722895],"study_design_scores_gemma":[0.00001409354,0.00003978064,0.004204474,0.00003037492,0.00002564356,0.000387625,0.0001386387,0.9416963,0.04552643,0.003791219,0.004104482,0.00004101665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06501327,0.0005694867,0.9289004,0.00007691576,0.00005402871,0.0001391156,0.0004361501,0.002772447,0.002038121],"genre_scores_gemma":[0.4608972,0.0009313055,0.5323945,0.00004813628,0.00005424106,0.0001153833,0.003260465,0.0002754239,0.002023327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006392717,"threshold_uncertainty_score":0.01271099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064171434893746,"score_gpt":0.2222475271376658,"score_spread":0.2016058127887283,"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."}}