{"id":"W4221152040","doi":"10.1109/lra.2022.3174971","title":"Intensity Image-Based LiDAR Fiducial Marker System","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Fiducial marker; Lidar; Point cloud; Coordinate system; Computer vision; Artificial intelligence; Intensity (physics); Computer science; Remote sensing; Physics; Optics; Geology","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":[0.0003020036,0.0003981897,0.0005223271,0.0008506638,0.000285142,0.0006106133,0.00124122,0.0005763461,0.002671673],"category_scores_gemma":[0.0008984755,0.0002406174,0.000276542,0.0005660949,0.0002042084,0.0008793121,0.001373626,0.0005486939,0.002133834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002793217,"about_ca_system_score_gemma":0.000559327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006890781,"about_ca_topic_score_gemma":0.0005421723,"domain_scores_codex":[0.9993902,0.00007032472,0.00003213013,0.000117243,0.0003395433,0.00005049282],"domain_scores_gemma":[0.9995897,0.0000324491,0.00006207664,0.00007602033,0.0002076098,0.00003212442],"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":[0.0002969252,0.00007113929,0.0024825,0.0003330128,0.00003098706,0.0002539116,0.0003319233,0.008803975,0.3260253,0.004812059,0.006498981,0.6500594],"study_design_scores_gemma":[0.0001550338,0.001031072,0.01007697,0.0001443669,0.0001083036,0.002965112,0.0002462367,0.4340167,0.439692,0.00332854,0.1079603,0.0002751762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02121338,0.0003314051,0.9699543,0.0001393686,0.0001085804,0.0001234231,0.0001932033,0.003663881,0.004272441],"genre_scores_gemma":[0.4573912,0.0005207999,0.5334345,0.0002976026,0.0001166315,0.0003319368,0.0008248523,0.0002000999,0.006882523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002671673,"threshold_uncertainty_score":0.008937597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006510953459521566,"score_gpt":0.1823857374736349,"score_spread":0.1758747840141133,"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."}}