{"id":"W2141869389","doi":"10.1109/ccece.2004.1345320","title":"An integrated robotic laser range sensing system for automatic mapping of wide workspaces","year":2004,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ontario Innovation Trust","keywords":"Workspace; Computer science; Process (computing); Orientation (vector space); Computer vision; Interface (matter); Range (aeronautics); Artificial intelligence; Position (finance); Laser; Robot; Real-time computing; 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":[0.0003988873,0.000494822,0.0006104835,0.0004889234,0.0004380161,0.0005989425,0.001688583,0.000613693,0.005561013],"category_scores_gemma":[0.0006066181,0.0003938146,0.0002552524,0.0005143988,0.0002883823,0.000891105,0.0007193129,0.0005275948,0.001622944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003302047,"about_ca_system_score_gemma":0.0007748566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001106431,"about_ca_topic_score_gemma":0.001538671,"domain_scores_codex":[0.9994815,0.00003826508,0.00001833414,0.0001227308,0.0002925753,0.00004661132],"domain_scores_gemma":[0.9996626,0.0000493232,0.00003667697,0.00007532791,0.0001303863,0.00004567884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007287466,0.0002637239,0.001326107,0.000221292,0.00005935931,0.0003667,0.0002445684,0.006705796,0.5075147,0.003594831,0.006285677,0.4726885],"study_design_scores_gemma":[0.0005894132,0.006006181,0.02010234,0.0001133642,0.0003723585,0.004769585,0.0001618072,0.3835482,0.4843624,0.002962281,0.09669725,0.0003148379],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1168273,0.0006439494,0.8555383,0.0001690381,0.0001845178,0.0002869294,0.0003070526,0.01776049,0.008282305],"genre_scores_gemma":[0.3858877,0.0002644137,0.6007596,0.0001553071,0.0000726736,0.0003165553,0.0004782162,0.0001918167,0.01187372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005561013,"threshold_uncertainty_score":0.0186035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01247623199650215,"score_gpt":0.2078488268241156,"score_spread":0.1953725948276135,"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."}}