{"id":"W2005660777","doi":"10.1068/a44450","title":"Smart Growth and Urban Economic Development: Connecting Economic Development and Land-Use Planning Using the Example of High-Tech Firms","year":2012,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Smart growth; Urban sprawl; Urban planning; Sustainable development; High tech; Business; Land use; Downtown; Growth management; Plan (archaeology); Environmental planning; Land-use planning; Economic growth; Economics; Geography; Engineering; Political science; Civil engineering","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":[0.0004785998,0.0002700437,0.0001741346,0.0008121127,0.003704278,0.004240953,0.0003903759,0.0009002905,0.002051381],"category_scores_gemma":[0.0006942466,0.0001131595,0.0002037253,0.001757943,0.006560795,0.001943057,0.002843892,0.001131791,0.0001380374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005639071,"about_ca_system_score_gemma":0.002494932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07748285,"about_ca_topic_score_gemma":0.2198356,"domain_scores_codex":[0.9993883,0.0003489136,0.000006920483,0.00002925086,0.00006445793,0.0001620727],"domain_scores_gemma":[0.9994888,0.0002985934,0.00003760133,0.00002910121,0.00005985798,0.00008596022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004308396,0.0001028227,0.01887644,0.00009918421,0.00001598415,0.002211538,0.02075724,0.008096905,0.0003448611,0.9272289,0.002498535,0.01972456],"study_design_scores_gemma":[0.00008739534,0.0001900809,0.05095826,0.0003449413,0.00006754258,0.001557637,0.1802943,0.02506416,0.00200838,0.3356406,0.403702,0.00008473296],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4822773,0.001672697,0.008844606,0.01036591,0.00004057166,0.00006268395,0.00006308612,0.00002131171,0.4966519],"genre_scores_gemma":[0.9891746,0.0009110699,0.00189843,0.0001460401,0.00000498174,0.00001325172,0.00001866481,0.000003326901,0.007829728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07748285,"threshold_uncertainty_score":0.1540637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05380961072825852,"score_gpt":0.2376188357225177,"score_spread":0.1838092249942592,"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."}}