{"id":"W2808647260","doi":"10.5198/jtlu.2018.1273","title":"Viewpoint: Integrated urban modeling: Past, present, and future","year":2018,"lang":"en","type":"article","venue":"Journal of Transport and Land Use","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Exploit; State (computer science); AKA; Urban planning; Land use; Computer science; Data science; Regional science; Management science; Operations research; Political science; Environmental planning; Engineering; Sociology; Computer security; Geography; Civil engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004827723,0.0001103481,0.000243949,0.00006969142,0.000246764,0.00006905591,0.0001224568,0.0001087485,0.0001238204],"category_scores_gemma":[0.00000455402,0.00007418341,0.00007983846,0.0001395995,0.000225649,0.0005955693,0.000003609911,0.0002103918,5.770024e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001066944,"about_ca_system_score_gemma":0.0000829718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007166163,"about_ca_topic_score_gemma":0.001522734,"domain_scores_codex":[0.9990423,0.00004163456,0.0003513495,0.0001348096,0.0002402579,0.0001896175],"domain_scores_gemma":[0.9993204,0.00002236401,0.0001265551,0.00007895689,0.000227869,0.0002238377],"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":[0.0001999042,0.00006124542,0.9883739,0.00001671066,0.00003936176,0.0000291569,0.007324561,0.000001660575,0.0000160806,0.0002497038,0.0009425992,0.002745138],"study_design_scores_gemma":[0.0008944294,0.0001712555,0.4399022,0.00007114553,0.0001443108,0.000007827136,0.001155538,0.0001845047,0.00001949037,0.0008976093,0.5563704,0.0001812821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934492,0.00122716,0.0004771592,0.003713807,0.0003020854,0.00008437103,0.0000119502,0.00001455395,0.00071978],"genre_scores_gemma":[0.994354,0.001002165,0.0002725561,0.0001499039,0.00391653,5.069508e-7,0.000004359693,0.000007515083,0.0002925351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5554278,"threshold_uncertainty_score":0.3025112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986665764187651,"score_gpt":0.2855416435479995,"score_spread":0.255674985906123,"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."}}