{"id":"W2967185040","doi":"10.1109/icra.2019.8793790","title":"Automated Seedling Height Assessment for Tree Nurseries Using Point Cloud Processing","year":2019,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Newfoundland and Labrador; Memorial University of Newfoundland","funders":"","keywords":"Point cloud; System of measurement; Cloud computing; Remote sensing; Computer science; Lidar; Photogrammetry; Laser scanning; Profilometer; Precision agriculture; Sample (material); Process (computing); Tree (set theory); Sampling (signal processing); Real-time computing; Artificial intelligence; Computer vision; Engineering; Mathematics; Optics; Laser; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002269903,0.000458619,0.000437318,0.0009514391,0.0003501417,0.0004469672,0.000820918,0.0003810942,0.001651427],"category_scores_gemma":[0.0004487237,0.0002220009,0.0002649687,0.0005576946,0.000112605,0.0005232395,0.0004470659,0.0002675361,0.0006482278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002995281,"about_ca_system_score_gemma":0.0004913594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002935086,"about_ca_topic_score_gemma":0.008953804,"domain_scores_codex":[0.9996731,0.00002627273,0.00001154227,0.00007192839,0.0001918785,0.00002524197],"domain_scores_gemma":[0.9995618,0.00009818769,0.00006549798,0.00006512582,0.000168642,0.00004066412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003434836,0.000174532,0.03221796,0.0002893419,0.00004991922,0.0004045094,0.000291586,0.01147151,0.5180023,0.0004577638,0.003656971,0.4326401],"study_design_scores_gemma":[0.0001350006,0.0006347203,0.1359384,0.00007246777,0.00009569561,0.0009872403,0.000384249,0.6053051,0.2458901,0.0009733803,0.009437367,0.0001462311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3080312,0.0002816706,0.6793078,0.00009951768,0.00007510377,0.0002883113,0.001094956,0.008406176,0.002415298],"genre_scores_gemma":[0.6416802,0.0001851193,0.3553865,0.0000644944,0.0000270004,0.00016873,0.000807807,0.0001353164,0.001544836],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002935086,"threshold_uncertainty_score":0.00583601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385317425739746,"score_gpt":0.2863459036868683,"score_spread":0.2724927294294708,"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."}}