{"id":"W2997460242","doi":"","title":"Extraction of tubular shapes from dense point clouds and application to tree reconstruction from laser scanned data","year":2017,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Point cloud; Tree (set theory); Laser; Computer science; Point (geometry); Laser scanning; Extraction (chemistry); Artificial intelligence; Computer vision; Optics; Geometry; Physics; Mathematics","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":[0.0005552677,0.0007946425,0.0008705416,0.00282575,0.0006055696,0.001611552,0.00110222,0.001306545,0.001651383],"category_scores_gemma":[0.002863221,0.001002984,0.001032543,0.003203924,0.0005425786,0.001013481,0.001267482,0.00095486,0.001817549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003300747,"about_ca_system_score_gemma":0.0008674002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003834607,"about_ca_topic_score_gemma":0.005983874,"domain_scores_codex":[0.9995474,0.00004490505,0.00003280314,0.00009787981,0.0002239906,0.00005304679],"domain_scores_gemma":[0.9983223,0.0006227131,0.000145816,0.0002543802,0.0005750075,0.00007970788],"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":[0.0002444023,0.0001538282,0.005641256,0.0003922806,0.00007589839,0.0007732343,0.0005932656,0.1285294,0.138407,0.003726293,0.003548861,0.7179142],"study_design_scores_gemma":[0.00001176727,0.00005859291,0.004167155,0.00003302938,0.0000243815,0.0006348938,0.0001756795,0.9504568,0.03714924,0.00360383,0.003645958,0.00003872947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04529205,0.0002174248,0.9497889,0.00008560103,0.00002560425,0.0001043915,0.0004541275,0.003361289,0.0006705744],"genre_scores_gemma":[0.1824962,0.0004611949,0.81299,0.00003156294,0.000030058,0.0001091274,0.002090993,0.0004881886,0.00130265],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003834607,"threshold_uncertainty_score":0.007624567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01325700241066595,"score_gpt":0.2355220456017668,"score_spread":0.2222650431911008,"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."}}