{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006551034,0.0001091554,0.0001432897,0.000009173674,0.0002856318,0.00004742097,0.0001381842,0.00008754421,0.0003320603],"category_scores_gemma":[0.0002738107,0.0000928115,0.00002760094,0.0001738137,0.00003216007,0.0004828532,0.0001822216,0.0001361434,0.00002701169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004833945,"about_ca_system_score_gemma":0.00002886543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007375104,"about_ca_topic_score_gemma":0.0002185679,"domain_scores_codex":[0.9988285,0.0002517931,0.0001931186,0.0003321971,0.0001524276,0.0002419811],"domain_scores_gemma":[0.999348,0.0001848953,0.00005905622,0.0001703753,0.00001123223,0.0002264702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001085635,0.000009940512,0.9929003,0.00006344701,0.000006331418,0.00000281383,0.002804063,0.0003288233,0.00001007776,0.0000910137,0.00004958535,0.003722768],"study_design_scores_gemma":[0.000187416,0.00007000597,0.9856101,0.000005713116,0.00002767694,8.615012e-7,0.002562545,0.003842958,0.0001005962,0.005818101,0.001595397,0.0001786577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913532,0.00008816054,0.004859312,0.001984857,0.00001824646,0.0003726257,0.000001901558,0.00006899872,0.001252734],"genre_scores_gemma":[0.9992461,0.000004031853,0.0005738653,0.00008900229,0.00005766523,0.000009720428,0.000002889675,0.000009207991,0.000007574538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007892879,"threshold_uncertainty_score":0.3784743,"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."}}