{"id":"W4293716502","doi":"10.3389/fenvs.2022.949442","title":"Assessing the effects of burn severity on post-fire tree structures using the fused drone and mobile laser scanning point clouds","year":2022,"lang":"en","type":"article","venue":"Frontiers in Environmental Science","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Forests, Lands, Natural Resource Operations and Rural Development","keywords":"Crown (dentistry); Point cloud; Laser scanning; Lidar; Tree (set theory); Environmental science; Forestry; Remote sensing; Physical geography; Geography; Meteorology; Atmospheric sciences; Computer science; Mathematics; Laser; Artificial intelligence; Geology; Medicine; Dentistry; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001482352,0.0002226204,0.0002330917,0.00006487004,0.001236218,0.00009651561,0.0008698457,0.00003989619,0.0001328515],"category_scores_gemma":[0.00007441846,0.0001503075,0.00005577219,0.0005454171,0.00201775,0.0005525509,0.001083051,0.0003857504,0.000002854609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173472,"about_ca_system_score_gemma":0.00002539427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007183255,"about_ca_topic_score_gemma":0.00001763662,"domain_scores_codex":[0.9971783,0.0003980618,0.0002722919,0.000581043,0.001084797,0.000485554],"domain_scores_gemma":[0.998991,0.0001957982,0.0002142998,0.000502736,0.000001602966,0.00009453536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007253032,0.0002990367,0.4369687,0.00004548768,0.00002100353,0.00004274235,0.007665925,0.04670724,0.4349512,0.000008522106,0.000442971,0.07277461],"study_design_scores_gemma":[0.0006589241,0.00048767,0.8442155,0.00004409049,0.00002646737,0.00005514062,0.008487966,0.1218058,0.02329101,0.000188007,0.0003932468,0.0003462307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975384,0.000280745,0.000176972,0.00008709243,0.0008700405,0.0008379821,0.00001284372,0.00001442648,0.0001815393],"genre_scores_gemma":[0.9986719,0.00001298331,0.0009152297,0.0002558505,0.00002211303,0.00006710026,0.000002112211,0.0000188705,0.00003381967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4116603,"threshold_uncertainty_score":0.9508118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003953351381710673,"score_gpt":0.2145287693153683,"score_spread":0.2105754179336576,"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."}}