{"id":"W7053080517","doi":"","title":"Sprawl and Smart Growth in Greater Vancouver: A Comparison of Vancouver, British Columbia, with Seattle, Washington","year":2002,"lang":"en","type":"article","venue":"Issue Lab (Candid)","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urban sprawl; Smart growth; Census; Growth management; Population growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004841446,0.0001147834,0.0002882449,0.00004674728,0.0000503626,0.00008603274,0.0001057583,0.00007718836,0.0001634517],"category_scores_gemma":[0.00001796816,0.0001574651,0.00002066014,0.0002386147,0.00005706575,0.00009992239,0.00002732146,0.0001492019,0.00001438341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003909159,"about_ca_system_score_gemma":0.00000535421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01131665,"about_ca_topic_score_gemma":0.4569674,"domain_scores_codex":[0.9991769,0.00001124365,0.0002391294,0.000197372,0.0001395693,0.0002358536],"domain_scores_gemma":[0.9995986,0.00007995729,0.00004183487,0.0001564454,0.00003904136,0.00008417362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006610591,0.0001807776,0.55609,0.0001867884,0.00005335157,0.00004035393,0.0007444528,0.001454356,0.0001481906,0.0000223159,0.4349856,0.006087208],"study_design_scores_gemma":[0.01071564,0.000774479,0.3037051,0.002556321,0.0003330669,0.00006905534,0.001338283,0.2082289,0.02147282,0.001079354,0.4470383,0.002688645],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922596,0.0004542563,0.0001019212,0.00004336597,0.0001642559,0.0002248212,0.00009084571,0.00009008907,0.006570858],"genre_scores_gemma":[0.9974614,0.0003610087,0.0008375688,0.00002956111,0.00003984174,0.00004849956,0.000007833331,0.00003521908,0.001179038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4456508,"threshold_uncertainty_score":0.9952671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007345672894676829,"score_gpt":0.1909388798405229,"score_spread":0.183593206945846,"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."}}