{"id":"W4315487774","doi":"10.1016/j.wss.2023.100127","title":"The role of urban and rural greenspaces in shaping immigrant wellbeing and settlement in place","year":2023,"lang":"en","type":"article","venue":"Wellbeing Space and Society","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Immigration; Settlement (finance); Geography; Diversity (politics); Neighbourhood (mathematics); Sociology; Economic growth; Business","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":[0.001789779,0.0002105929,0.0002404466,0.0006813951,0.006055865,0.004783042,0.0005379056,0.0005946559,0.005581936],"category_scores_gemma":[0.00266422,0.0001420222,0.0003394705,0.0008167019,0.006496122,0.001752194,0.006241285,0.001113192,0.0002591548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00248606,"about_ca_system_score_gemma":0.003953137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0541815,"about_ca_topic_score_gemma":0.1716751,"domain_scores_codex":[0.999028,0.000467313,0.0000266232,0.00008696888,0.0001113802,0.0002797362],"domain_scores_gemma":[0.9990689,0.0002631187,0.0001311608,0.00007709286,0.0001181742,0.0003416011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000125793,0.0001399349,0.2160608,0.0003537379,0.00009463938,0.002160551,0.6537936,0.0006166577,0.001914274,0.04309741,0.00337433,0.07826816],"study_design_scores_gemma":[0.000007381841,0.0000849586,0.1352669,0.0004447004,0.00004209231,0.0003605553,0.8151105,0.0002863268,0.0002161432,0.00912055,0.03900281,0.00005704748],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629762,0.0007824636,0.0013487,0.002484121,0.00007501911,0.00003005924,0.00007965024,0.00001195645,0.03221162],"genre_scores_gemma":[0.99775,0.0003666383,0.0004609711,0.0002096157,0.000007686677,0.00001402443,0.00002132571,0.00000754557,0.001162149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0541815,"threshold_uncertainty_score":0.1077323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007715958105333345,"score_gpt":0.2247359187604649,"score_spread":0.2170199606551316,"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."}}