{"id":"W2065817363","doi":"10.1007/s11205-007-9185-4","title":"The Quality of the Urban Environment Around Public Housing Buildings in Montréal: An Objective Approach Based on GIS and Multivariate Statistical Analysis","year":2007,"lang":"en","type":"article","venue":"Social Indicators Research","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Built environment; Public housing; Census; Public space; Human geography; Urban planning; Environmental planning; Geographic information system; Environmental resource management; Geography; Business; Civil engineering; Architectural engineering; Cartography; Sociology; Population; Engineering; Environmental science","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":[0.0009058081,0.0003446964,0.0002922977,0.002882065,0.0009080907,0.00149369,0.0004871006,0.0001717998,0.001118578],"category_scores_gemma":[0.002276045,0.0002207074,0.000404309,0.004289835,0.0008103452,0.0005534054,0.0006490438,0.0002553037,0.0000946805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005273819,"about_ca_system_score_gemma":0.003039246,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8245819,"about_ca_topic_score_gemma":0.9089862,"domain_scores_codex":[0.9993692,0.0001915206,0.00003369021,0.00007485542,0.0002539892,0.00007672797],"domain_scores_gemma":[0.9987994,0.0002211913,0.0003333178,0.00004495805,0.000479645,0.0001215506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000168804,0.00004222745,0.9774884,0.00007409452,0.0002262637,0.00006427849,0.001175974,0.003478456,0.00114545,0.0008444865,0.0009000394,0.01439161],"study_design_scores_gemma":[0.000003923726,0.00004099087,0.9962518,0.000005003015,0.00003320751,0.00001170345,0.0006134653,0.002346549,0.0002147698,0.00006370327,0.0004001072,0.00001495094],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929974,0.0001874452,0.001987947,0.00006957724,0.00000690609,0.00005479862,0.001942786,0.00003323745,0.002719928],"genre_scores_gemma":[0.9976445,0.00007753489,0.0012493,0.000004461297,0.000006123423,0.00002653031,0.0004487026,0.000007102746,0.0005357443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1754181,"threshold_uncertainty_score":0.3529023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09624034357687568,"score_gpt":0.4248365200489131,"score_spread":0.3285961764720375,"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."}}