{"id":"W2897219677","doi":"10.1111/cag.12496","title":"Path dependencies affecting suburban density, mix, and diversity in Halifax","year":2018,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Urbanization and City Planning","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Dalhousie University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Nova scotia; Diversity (politics); Politics; Subdivision; Resistance (ecology); Economic geography; Path (computing); Geography; Land use; Path dependence; Path dependent; Population growth; Economic growth; Population; Business; Political science; Sociology; Economics; Computer science; Engineering; Ecology; Civil engineering; Demography; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007179091,0.0002522876,0.0002823743,0.002756491,0.003684716,0.0002419405,0.0004068398,0.0002203507,0.0001157668],"category_scores_gemma":[0.0003914267,0.0002967781,0.00009631677,0.004451566,0.002665014,0.0004339217,0.0001489448,0.0002217514,0.000007730247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595873,"about_ca_system_score_gemma":0.0002573796,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9641466,"about_ca_topic_score_gemma":0.9998018,"domain_scores_codex":[0.9975939,0.0001963948,0.0002328402,0.0004868551,0.0003155262,0.001174439],"domain_scores_gemma":[0.9981722,0.0001598621,0.00009098717,0.000233609,0.0002629002,0.001080454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006171755,0.000008733009,0.9519054,0.00001474343,0.00003060153,0.00008011536,0.02917923,4.737853e-7,0.000006974766,0.01383487,0.003723606,0.001209085],"study_design_scores_gemma":[0.0003060584,0.00009054474,0.8743762,0.00008099244,0.0000368992,0.00001758068,0.09221729,0.00001292015,0.00001501649,0.002425583,0.0298618,0.0005590462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847137,0.0007472774,0.000004629632,0.001030665,0.0005599324,0.0002696016,0.00004657703,0.0001128716,0.01251478],"genre_scores_gemma":[0.9980141,0.0005846683,0.00008779742,0.0007094811,0.0002159284,0.000006927482,0.00002032806,0.00002004072,0.0003407455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07752912,"threshold_uncertainty_score":0.9999484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580145366051735,"score_gpt":0.2152992546932023,"score_spread":0.199497801032685,"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."}}