{"id":"W2130726392","doi":"10.1109/imtc.2005.1604520","title":"An Integrated Robotic Multi-Modal Range Sensing System","year":2006,"lang":"en","type":"article","venue":"2005 IEEE Instrumentationand Measurement Technology Conference Proceedings","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ontario Innovation Trust","keywords":"Computer science; Workspace; Artificial intelligence; Computer vision; Range (aeronautics); Process (computing); Orientation (vector space); Overhead (engineering); Calibration; Robot; Engineering","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":[0.0004628709,0.0006054398,0.0006321625,0.0005815449,0.0005090803,0.0008785399,0.001951379,0.0009334739,0.005675863],"category_scores_gemma":[0.0005993256,0.0003414832,0.0003940368,0.0003929517,0.0002635409,0.001234035,0.001603739,0.0006000947,0.002461703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000379217,"about_ca_system_score_gemma":0.0006279775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001133027,"about_ca_topic_score_gemma":0.001369055,"domain_scores_codex":[0.9990929,0.00005475052,0.00003997059,0.0002773826,0.0004584314,0.00007652657],"domain_scores_gemma":[0.9996151,0.0000373662,0.00004348397,0.00009744002,0.0001537119,0.00005292839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006157656,0.0004381019,0.001713309,0.0003138147,0.0001102277,0.0004130051,0.0002992267,0.02884549,0.3774166,0.0083233,0.01022518,0.5712861],"study_design_scores_gemma":[0.0002208797,0.002165222,0.006134081,0.00008641075,0.0002560378,0.002106793,0.0001502312,0.6975536,0.1875832,0.006702762,0.09673972,0.0003011309],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03136726,0.0002923356,0.9446692,0.0002176907,0.0002237897,0.0002196262,0.0002168881,0.01210565,0.0106875],"genre_scores_gemma":[0.4529397,0.0002387025,0.5270607,0.0004922667,0.0001477106,0.0005002902,0.0006293629,0.0001763763,0.01781474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005675863,"threshold_uncertainty_score":0.0189876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02849088320467803,"score_gpt":0.2541377313301285,"score_spread":0.2256468481254504,"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."}}