{"id":"W7132925200","doi":"","title":"Urban forest monitoring in the Regional Municipality of Peel's heat vulnerable areas","year":2020,"lang":"en","type":"other","venue":"TSpace","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Urban heat island; Urban forest; Tree planting; Urban forestry; Urban ecosystem; Climate change; Urban climate; Green infrastructure","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002508587,0.0001055902,0.00009399277,0.0007940052,0.0007700998,0.0004468782,0.000314363,0.0002091137,0.0009995564],"category_scores_gemma":[0.0008445354,0.0001315194,0.0001037004,0.000755856,0.0002321979,0.0002603887,0.0005810587,0.0002153825,0.0001492559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007383557,"about_ca_system_score_gemma":0.0008241851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08586515,"about_ca_topic_score_gemma":0.3266476,"domain_scores_codex":[0.9998547,0.00003797358,0.000005967008,0.00003430843,0.00002720608,0.00003982239],"domain_scores_gemma":[0.9995182,0.00009681749,0.0001274141,0.00003170495,0.0001241851,0.0001017773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001341899,0.00008471336,0.9409128,0.0001035194,0.00002897335,0.001797011,0.008644897,0.0006658055,0.004768989,0.0002188756,0.001668981,0.04097115],"study_design_scores_gemma":[0.000003702188,0.00009273239,0.9875673,0.00001898211,0.000009381515,0.0002584687,0.008567981,0.0007208969,0.0005414756,0.00004614812,0.002165179,0.000007729951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998201,0.00003688316,0.0001444591,0.00007509377,0.000001397383,0.00004375981,0.0002110072,0.000009816559,0.001276613],"genre_scores_gemma":[0.9973198,0.00007090458,0.001172084,0.00002026568,0.000002283887,0.00005639984,0.0002181173,0.000002482656,0.001137794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08586515,"threshold_uncertainty_score":0.1707307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064116978401697,"score_gpt":0.3833820382243892,"score_spread":0.2769703403842195,"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."}}