{"id":"W4396850241","doi":"10.1016/j.landurbplan.2024.105102","title":"Managing urban trees through storms in three United States cities","year":2024,"lang":"en","type":"article","venue":"Landscape and Urban Planning","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"University of Florida; Tree Research and Education Endowment Fund; U.S. Department of Agriculture","keywords":"Geography; Storm; Environmental planning; Meteorology","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":[0.0007431853,0.0002344135,0.000238838,0.0003647138,0.005540732,0.00250858,0.001214416,0.0008037738,0.001525879],"category_scores_gemma":[0.001118617,0.0002626953,0.0002633586,0.0009939423,0.0011457,0.0005626418,0.001997266,0.0008781722,0.0001401952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006712871,"about_ca_system_score_gemma":0.007978146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2176941,"about_ca_topic_score_gemma":0.6939735,"domain_scores_codex":[0.9994203,0.0001608979,0.00001865476,0.00004890436,0.0001149333,0.0002362285],"domain_scores_gemma":[0.9988256,0.0001845715,0.0001480252,0.00008456637,0.000288313,0.000468937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00206545,0.004653072,0.5894293,0.000351957,0.0003570028,0.003629059,0.05989417,0.07662075,0.01500598,0.01215105,0.0389837,0.1968585],"study_design_scores_gemma":[0.0003086874,0.001594759,0.644685,0.00009775944,0.0002929249,0.000310031,0.2316467,0.03173494,0.005546246,0.003090069,0.08053697,0.0001558239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940237,0.0000490099,0.0003218545,0.0004501833,0.00001096343,0.0000730621,0.00009601624,0.00002848055,0.004946603],"genre_scores_gemma":[0.9956927,0.000106947,0.001391148,0.00008788925,0.000004262432,0.0000504965,0.0001243413,0.00001369201,0.002528542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2176941,"threshold_uncertainty_score":0.4328539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187256377015619,"score_gpt":0.2487727590068499,"score_spread":0.230047121305288,"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."}}