{"id":"W1992204148","doi":"10.1115/1.1876492","title":"Total Least-Squares Methods for Active View Registration of Three-Dimensional Line Laser Scanning Data","year":2004,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Toronto Metropolitan University","funders":"","keywords":"Laser scanning; Least-squares function approximation; Transformation (genetics); Position (finance); Line (geometry); Point cloud; Total least squares; Algorithm; Point (geometry); Computer science; Mathematics; Artificial intelligence; Laser; Statistics; Optics; Geometry","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":[0.002037781,0.001205468,0.001324452,0.001401087,0.0005898876,0.001108398,0.001937237,0.001038593,0.001805146],"category_scores_gemma":[0.006169565,0.0008937292,0.001396337,0.001952601,0.0008592866,0.001577109,0.00145117,0.001659299,0.001439416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004612335,"about_ca_system_score_gemma":0.001139083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002363263,"about_ca_topic_score_gemma":0.002630542,"domain_scores_codex":[0.997792,0.0007212583,0.0001344888,0.0004355068,0.000841376,0.00007522482],"domain_scores_gemma":[0.9972768,0.001238019,0.0002972648,0.0004194917,0.0007147932,0.00005369161],"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":[0.0002501331,0.0001033589,0.0009027353,0.0003987015,0.0002472069,0.0001043939,0.000411329,0.2713279,0.03421776,0.01726763,0.003090796,0.6716781],"study_design_scores_gemma":[0.00001573053,0.0000672113,0.0004331721,0.00001698827,0.00002457755,0.0001073599,0.0000519659,0.9791302,0.01054308,0.006062063,0.003501992,0.00004558574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009688784,0.00006203095,0.9985989,0.00001449196,0.00001034476,0.00001184853,0.00001334552,0.0002217632,0.0000985097],"genre_scores_gemma":[0.05171785,0.0002162509,0.9461703,0.00004107364,0.00003079085,0.0002011661,0.0002107623,0.0002572271,0.001154606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002363263,"threshold_uncertainty_score":0.01077694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184820900864548,"score_gpt":0.3780958909377175,"score_spread":0.2596138008512627,"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."}}