{"id":"W1986976726","doi":"10.1016/s0007-8506(07)60613-1","title":"Computer-Aided Planning of Laser Scanning of Complex Geometries","year":2003,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Laser scanning; CAD; Visibility; Plan (archaeology); Scanner; Computer Aided Design; Computer science; Motion planning; Computer-aided; Artificial intelligence; Computer vision; Engineering drawing; Laser; Engineering; Optics; Robot","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":[0.0005618869,0.0006718122,0.00073036,0.000914381,0.0005026578,0.0009233583,0.0007673067,0.0007931439,0.002518889],"category_scores_gemma":[0.001970996,0.000897389,0.0005766263,0.0008194638,0.0007060788,0.0007270739,0.0007305177,0.0006078873,0.0004134862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006878853,"about_ca_system_score_gemma":0.00202219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007660508,"about_ca_topic_score_gemma":0.01591944,"domain_scores_codex":[0.999593,0.0001145839,0.00002055403,0.00006490284,0.0001742584,0.0000329125],"domain_scores_gemma":[0.9987123,0.0009569033,0.00007982743,0.0001150589,0.0001060861,0.000029839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002910768,0.00007064706,0.001036894,0.0001906452,0.00003955578,0.0002775374,0.000355475,0.7777688,0.02913127,0.008392643,0.001972318,0.1804733],"study_design_scores_gemma":[0.00001551628,0.00004351171,0.0004779922,0.00001234967,0.000008560931,0.0001690648,0.00003798812,0.9837747,0.01130398,0.00255972,0.001580112,0.00001666271],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05429085,0.0003404657,0.94115,0.00007482248,0.00001559112,0.000122034,0.0001305845,0.001312393,0.002563307],"genre_scores_gemma":[0.4100912,0.0003658662,0.5871949,0.00002217203,0.000007901474,0.0001659816,0.0001891162,0.0001558038,0.001807142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007660508,"threshold_uncertainty_score":0.01523185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0936967195489951,"score_gpt":0.2942839058475865,"score_spread":0.2005871862985913,"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."}}