{"id":"W3003634620","doi":"10.3390/su12030997","title":"Showcasing Relationships between Neighborhood Design and Wellbeing Toronto Indicators","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Landscape ecology; Geography; Land use; Sustainability; Environmental resource management; Urbanization; Landscape planning; Land cover; Sustainable development; Cohesion (chemistry); Ecology; Green infrastructure; Urban planning; Regional science; Environmental planning; Environmental 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":[0.000398594,0.0002427855,0.0001859273,0.001549835,0.0004619558,0.0008077399,0.0002182419,0.0001184137,0.002786045],"category_scores_gemma":[0.002533857,0.0001105859,0.0002395379,0.002922426,0.0003750578,0.0003264376,0.0008645131,0.0002117412,0.0002275193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002152187,"about_ca_system_score_gemma":0.0010327,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3806911,"about_ca_topic_score_gemma":0.7078292,"domain_scores_codex":[0.9996907,0.00005412298,0.00002436654,0.00005169783,0.0001281863,0.00005104089],"domain_scores_gemma":[0.9985456,0.0003572973,0.0003706565,0.0001282251,0.0004031867,0.0001950552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004326541,0.00000544874,0.9895461,0.00003219194,0.00004179206,0.00004043246,0.00116278,0.0007261682,0.0002369007,0.0004997309,0.001250412,0.006414808],"study_design_scores_gemma":[6.036489e-7,0.000009778842,0.9965939,0.000008405805,0.00001118227,0.00001519991,0.001111673,0.0008628748,0.0001080564,0.00007175985,0.001201982,0.00000460197],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894455,0.0001585815,0.000737206,0.00009753399,0.000005219595,0.00001208183,0.005180512,0.00003399036,0.004329392],"genre_scores_gemma":[0.9965668,0.00007619286,0.0004782062,0.000003362078,0.000002579191,0.00001277514,0.002364879,0.000005593871,0.0004895584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6193089,"threshold_uncertainty_score":0.7569505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013128408695991,"score_gpt":0.2346001170908073,"score_spread":0.2144688330038474,"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."}}