{"id":"W4417054950","doi":"10.1016/j.ufug.2025.129223","title":"Exploring the impact of ice storm on urban forests and branch fall using mobile LiDAR","year":2025,"lang":"en","type":"article","venue":"Urban forestry & urban greening","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Storm; Lidar; Bridge (graph theory); Pruning; Tree (set theory); Forest structure","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002237055,0.0004231576,0.0004936354,0.0002299858,0.0003190525,0.00006983239,0.0003088375,0.0001009589,0.000006311344],"category_scores_gemma":[0.00009307003,0.0003282696,0.0002488858,0.0004921014,0.0001814848,0.000350244,0.0001521543,0.0004460979,0.000002710772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002195273,"about_ca_system_score_gemma":0.00004666529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007980692,"about_ca_topic_score_gemma":0.001934091,"domain_scores_codex":[0.9982954,0.00004455723,0.0004664687,0.0003691467,0.0002562129,0.0005682281],"domain_scores_gemma":[0.9987735,0.0003976389,0.00008642793,0.0005678102,0.00006864624,0.0001059412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006780225,0.00003324832,0.9634805,0.0001832382,0.0002901082,0.000005028629,0.003494698,0.0268847,0.0004140561,0.0002495448,0.001649609,0.003247504],"study_design_scores_gemma":[0.0006210508,0.0002496981,0.9765183,0.0004325442,0.0001016315,0.000004587297,0.0004630327,0.0189766,0.001011942,0.0002032571,0.001027784,0.00038951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935077,0.003719101,0.0008504721,0.00001659409,0.0003534737,0.0004149856,0.00003115052,0.0002301583,0.0008763126],"genre_scores_gemma":[0.9993287,0.00002826074,0.0001188645,0.000006843366,0.0002289973,0.0000703479,0.000005750036,0.00005763185,0.0001546382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0130379,"threshold_uncertainty_score":0.9999169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947317261317838,"score_gpt":0.2593139670037951,"score_spread":0.2198407943906167,"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."}}