{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008398506,0.0001354602,0.0001887893,0.00003163506,0.0002638175,0.00003758454,0.00008553302,0.00007249697,0.000008019116],"category_scores_gemma":[0.00001247688,0.0001074119,0.00003580342,0.0002938739,0.0003266557,0.0001332499,0.0002278909,0.0001902056,0.000004370299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006053836,"about_ca_system_score_gemma":0.00001094924,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009955872,"about_ca_topic_score_gemma":0.01406454,"domain_scores_codex":[0.9989049,0.00005298781,0.0001982861,0.0002508589,0.0001938006,0.0003991286],"domain_scores_gemma":[0.9995413,0.000176315,0.00007413643,0.0001265406,0.00000318333,0.00007847921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001161596,0.000009457783,0.9674094,0.00003312068,0.000007150652,0.0000024627,0.02659199,0.00008434722,0.002989989,0.0004326346,0.001150329,0.001277507],"study_design_scores_gemma":[0.0005509408,0.00005577998,0.9243098,0.000120491,0.000008616975,0.000001970776,0.05342602,0.01531771,0.000151765,0.000766469,0.005119441,0.0001709497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941019,0.002002627,0.000002629379,0.003268004,0.00002289378,0.0002022408,0.000003970148,0.00001923933,0.0003764352],"genre_scores_gemma":[0.9943061,0.004933922,0.0001715774,0.0001236474,0.00002020774,0.000009333122,0.000002494333,0.00001162437,0.000421077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04309955,"threshold_uncertainty_score":0.9966369,"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."}}