{"id":"W2536640939","doi":"10.1109/tgrs.2016.2617819","title":"Road Curb Extraction From Mobile LiDAR Point Clouds","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Lidar; Point cloud; Point (geometry); Extraction (chemistry); Correctness; Feature extraction","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":[0.0002544852,0.001509031,0.001269602,0.004714618,0.0007080812,0.001034755,0.001193865,0.001072077,0.001308118],"category_scores_gemma":[0.001350903,0.0007621471,0.001054109,0.002601026,0.0003435654,0.001237679,0.001562615,0.000882215,0.002066499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000408162,"about_ca_system_score_gemma":0.000882191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00818743,"about_ca_topic_score_gemma":0.01516062,"domain_scores_codex":[0.9992643,0.00003822839,0.00003532421,0.0001261996,0.0004273832,0.0001084314],"domain_scores_gemma":[0.9991842,0.00009425917,0.0001096323,0.0001464699,0.0004310956,0.00003444861],"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":[0.0001966483,0.00009033878,0.009513128,0.0009619929,0.0001743077,0.001312108,0.0003871623,0.04382945,0.1692113,0.002395112,0.01069225,0.7612362],"study_design_scores_gemma":[0.00003427091,0.00009388299,0.02010164,0.0002088905,0.0001059314,0.001546705,0.0005696736,0.7548692,0.1836843,0.004182187,0.03447642,0.0001268283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07329379,0.001082921,0.9127554,0.0001188377,0.00009452149,0.0003494195,0.001464431,0.007912833,0.002927842],"genre_scores_gemma":[0.3865004,0.001613811,0.601934,0.0001081156,0.0000526793,0.0002678265,0.005343066,0.0008016865,0.003378491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00818743,"threshold_uncertainty_score":0.01627958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009914237363220947,"score_gpt":0.2399610230494847,"score_spread":0.2300467856862638,"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."}}