{"id":"W3199112799","doi":"10.1080/02697459.2021.1979786","title":"Smart Growth in Canada’s Provincial North","year":2021,"lang":"en","type":"article","venue":"Planning Practice and Research","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; University of Northern British Columbia","keywords":"Smart growth; Neighbourhood (mathematics); Sustainability; Context (archaeology); Urban sustainability; Smart city; Sustainable growth rate; Growth management; Geography; Capital (architecture); Economic geography; Capital city; Regional science; Environmental planning; Urban planning; Economic growth; Business; Economics; Land use; Internet of Things; Engineering; Civil engineering; Computer science; Ecology; Computer security","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":[0.001922303,0.00004707431,0.00008909547,0.00005737802,0.0005277475,0.000116059,0.000127506,0.00004222399,0.00006575787],"category_scores_gemma":[0.002831046,0.00004458977,0.00001031752,0.0005041442,0.00012475,0.0004478368,0.00004457697,0.0005171504,0.000004061086],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002077651,"about_ca_system_score_gemma":0.008133007,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9800396,"about_ca_topic_score_gemma":0.9967147,"domain_scores_codex":[0.9980205,0.0005200992,0.0001275525,0.0002298482,0.0007056961,0.0003963368],"domain_scores_gemma":[0.9984066,0.001037259,0.00002799049,0.00008132518,0.0003177328,0.0001290973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004015453,0.00004230972,0.9913982,0.00002391674,0.000005124863,0.000613326,0.004953431,0.000001055334,0.000007271823,0.0003011222,0.00140579,0.001208344],"study_design_scores_gemma":[0.0001423528,0.00001106551,0.9027387,0.00002613369,0.00000447598,0.000001603919,0.014465,0.000009398886,0.00005908929,0.0001659615,0.08230118,0.00007503137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9325184,0.00062507,0.000003006,0.009318772,0.00009698905,0.0001064319,0.000004753621,0.0000087266,0.0573178],"genre_scores_gemma":[0.998544,0.0001317944,0.0000934281,0.0001680787,0.0001379396,0.000006662307,0.000008181728,0.00000393751,0.0009059444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08865944,"threshold_uncertainty_score":0.9974899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08596645768354944,"score_gpt":0.4059902330930386,"score_spread":0.3200237754094892,"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."}}