{"id":"W4238831069","doi":"10.32920/ryerson.14652969","title":"Urban forest vulnerability and its implications for ecosystem service supply at multiple scales","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Fulbright Canada; U.S. Forest Service; Syracuse University; Northern Research Station; University of Toronto; U.S. Department of Agriculture","keywords":"Ecosystem services; Urban ecosystem; Environmental resource management; Vulnerability (computing); Urban forest; Geography; Forest ecology; Urban ecology; Urban planning; Vulnerability assessment; Spatial ecology; Urban forestry; Temporal scales; Ecosystem; Environmental planning; Ecology; Environmental science; Urbanization; Psychological resilience; Forestry; Computer science","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":[0.0007018145,0.00018653,0.0002312702,0.00137182,0.001001625,0.001830113,0.0002766639,0.0003086425,0.002103231],"category_scores_gemma":[0.0031754,0.0001293591,0.0002614337,0.001846663,0.001562772,0.00181459,0.002324991,0.000585691,0.00008235451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002583473,"about_ca_system_score_gemma":0.0009040534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01613093,"about_ca_topic_score_gemma":0.02939172,"domain_scores_codex":[0.9995102,0.0001647522,0.00002010652,0.00004929639,0.00009177899,0.0001639098],"domain_scores_gemma":[0.9977074,0.0009982282,0.0006449956,0.00008657474,0.0002905517,0.0002723064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001220058,0.0001005179,0.7758663,0.0001489115,0.0001718305,0.001266593,0.009460344,0.05846579,0.001362201,0.1008517,0.001463131,0.05072064],"study_design_scores_gemma":[0.000003096296,0.00007237899,0.8562552,0.0001436795,0.00006634596,0.0004826392,0.02930479,0.03177488,0.0004030498,0.0773064,0.004148687,0.00003882324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839395,0.0004544148,0.001933259,0.001129044,0.000005934179,0.00001471798,0.0001236212,0.000006843819,0.01239256],"genre_scores_gemma":[0.9993661,0.0001950528,0.0001500353,0.00001407574,0.000003448534,0.000004823913,0.00001839907,0.000001374724,0.0002467159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01613093,"threshold_uncertainty_score":0.03207403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297007451390745,"score_gpt":0.246714551839968,"score_spread":0.2237444773260605,"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."}}