{"id":"W3004062346","doi":"","title":"Toronto in deep: the ravines in one of the world's largest urban forests need help against fragmentation, neglect, invasive plants, and now climate change","year":2019,"lang":"en","type":"article","venue":"Landscape architecture","topic":"Botany and Plant Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Ravine; Climate change; Fragmentation (computing); Geography; Neglect; Forest fragmentation; Environmental resource management; Environmental planning; Environmental protection; Ecology; Environmental science; Archaeology; Habitat; Biology","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":[0.0004485903,0.0002607708,0.0002128951,0.000274789,0.01036967,0.003770977,0.000643881,0.002424059,0.01728663],"category_scores_gemma":[0.001307635,0.0002178419,0.0001527906,0.0008065155,0.003397544,0.001772751,0.001630664,0.003759769,0.0009537975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01253692,"about_ca_system_score_gemma":0.01880688,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8164982,"about_ca_topic_score_gemma":0.9751467,"domain_scores_codex":[0.9996777,0.00007737657,0.000009146034,0.00003391721,0.00006512381,0.0001367953],"domain_scores_gemma":[0.9983876,0.0001039548,0.00008223295,0.00003980843,0.0002125991,0.001173891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002061061,0.00007281853,0.04478442,0.0003553431,0.00007167618,0.004266349,0.04437242,0.0004967367,0.003953923,0.02885663,0.7533683,0.1191953],"study_design_scores_gemma":[0.00002256675,0.00004167065,0.09002686,0.0001811095,0.00004993677,0.0005644475,0.1214479,0.0001776149,0.0005095523,0.005598935,0.7813205,0.00005895303],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1575406,0.01333192,0.001387994,0.7115659,0.005300298,0.00005750413,0.000825885,0.000242028,0.1097479],"genre_scores_gemma":[0.8267297,0.008816561,0.002743844,0.06729728,0.001245871,0.00002250914,0.0003305865,0.0001416968,0.09267197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1835018,"threshold_uncertainty_score":0.3691649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009952554045238277,"score_gpt":0.1941646590197781,"score_spread":0.1842121049745398,"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."}}