{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005462106,0.0004722413,0.0003825092,0.001818325,0.0003577365,0.001038839,0.0006250243,0.000485825,0.0007146819],"category_scores_gemma":[0.00126618,0.000397204,0.000754962,0.001203154,0.0003246726,0.0006499794,0.000615689,0.000532597,0.0002783577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117267,"about_ca_system_score_gemma":0.0008603705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09806326,"about_ca_topic_score_gemma":0.202986,"domain_scores_codex":[0.9995574,0.00003270926,0.00001977811,0.000123921,0.000171144,0.00009506584],"domain_scores_gemma":[0.9995027,0.0001059916,0.00008180341,0.00006042687,0.0001992914,0.00004977205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004503125,0.0003253482,0.5808588,0.0001401373,0.0003261902,0.0003877546,0.0006990138,0.2624106,0.0366994,0.00103066,0.001318813,0.115353],"study_design_scores_gemma":[0.00001764401,0.00006905293,0.3877319,0.00003637404,0.00007555978,0.0001701574,0.0003802636,0.6029537,0.006974957,0.0003683422,0.001160551,0.00006152494],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862925,0.0001461132,0.010463,0.00005946501,0.00001125103,0.00003358367,0.00150926,0.0003727372,0.001112114],"genre_scores_gemma":[0.9869717,0.00008243703,0.01074327,0.00001727826,0.000004439218,0.00001589521,0.001888359,0.00003231299,0.0002442047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09806326,"threshold_uncertainty_score":0.1949849,"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."}}