{"id":"W7107871347","doi":"10.1016/j.ufug.2025.129192","title":"Variability and bias in likelihood of urban tree failure ratings","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":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Credential; Tree (set theory); Risk perception; Perception; Test (biology); Risk assessment","routes":{"ca_aff":true,"ca_fund":false,"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":[0.04820012,0.000393257,0.0005922305,0.001950175,0.0008597985,0.001515957,0.001005659,0.000528108,0.002475087],"category_scores_gemma":[0.1306226,0.0003036385,0.0009372159,0.00149862,0.001310883,0.001217783,0.002137447,0.0008746777,0.0006719333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059734,"about_ca_system_score_gemma":0.0008692464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0107526,"about_ca_topic_score_gemma":0.01564771,"domain_scores_codex":[0.9366605,0.03809814,0.005396602,0.004172001,0.01415907,0.001513665],"domain_scores_gemma":[0.8381002,0.09109311,0.0273682,0.01584335,0.02544611,0.002149037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007957083,0.0001886807,0.9113455,0.0004502883,0.0002966968,0.0001602041,0.02550206,0.0007253361,0.001507568,0.0007978564,0.003262665,0.05496742],"study_design_scores_gemma":[0.00005278016,0.0006258926,0.9632378,0.000500233,0.0001280741,0.0003963933,0.01864836,0.003863458,0.00230797,0.00196208,0.008138247,0.0001386228],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837504,0.0004540692,0.00828317,0.0003378523,0.0001048223,0.0004900254,0.0007883831,0.00006789867,0.005723408],"genre_scores_gemma":[0.9951164,0.0001508474,0.002801795,0.000165149,0.00004169834,0.0005306987,0.00039646,0.00002451303,0.0007723639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04820012,"threshold_uncertainty_score":0.2549096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119764193499114,"score_gpt":0.2110399543760306,"score_spread":0.1998423124410394,"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."}}