{"id":"W2351004905","doi":"","title":"Roof Detection Using LiDAR Data Based on Points' Normal with Weight","year":2009,"lang":"en","type":"article","venue":"Wuhan Daxue xuebao. Xinxi kexue ban","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Roof; Lidar; Point (geometry); Plane (geometry); Computer science; Remote sensing; Mathematics; Geometry; Geology; Structural engineering; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004050361,0.0003151057,0.0002834466,0.0002263467,0.0004154612,0.000221012,0.0004775332,0.0001419277,0.0003534043],"category_scores_gemma":[0.00005596206,0.0002331095,0.00005766599,0.0004639493,0.00006912991,0.0005159675,0.00001584785,0.0003436056,0.0001788493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000015612,"about_ca_system_score_gemma":0.0001139245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170052,"about_ca_topic_score_gemma":0.005035518,"domain_scores_codex":[0.997856,0.0001515516,0.0002816265,0.000663556,0.0004926996,0.0005545223],"domain_scores_gemma":[0.9983926,0.00009934561,0.0001376792,0.001066313,0.00005070474,0.0002532923],"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":[0.002728035,0.0003719383,0.1525875,0.00009577835,0.0001112229,0.0007261097,0.0004686174,0.04358756,0.001658835,0.0000385378,0.001476766,0.7961491],"study_design_scores_gemma":[0.001534021,0.001377073,0.3064964,0.0002220779,0.00009121965,0.0001717207,0.00005824512,0.6581263,0.003275225,0.00008883882,0.02782393,0.0007349362],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836862,0.000119042,0.002634103,0.000745328,0.0005059099,0.0002519312,0.0001271576,0.0001806231,0.0117497],"genre_scores_gemma":[0.9941538,0.000009006852,0.003655643,0.0009358884,0.0005412134,9.256053e-8,0.0004227861,0.000013492,0.0002680699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7954141,"threshold_uncertainty_score":0.9505928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02138780844890805,"score_gpt":0.2167517816232795,"score_spread":0.1953639731743715,"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."}}