{"id":"W4311192247","doi":"10.3390/urbansci6040088","title":"Towards a Model of Urban Evolution: Part II: Formal Model","year":2022,"lang":"en","type":"article","venue":"Urban Science","topic":"Urban Design and Spatial Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Similarity (geometry); Signature (topology); Space (punctuation); Computer science; Physical space; Measure (data warehouse); Theoretical computer science; Urban planning; Geography; Data science; Data mining; Artificial intelligence; Mathematics; Cartography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004731891,0.0001181712,0.000175273,0.000236227,0.0004903138,0.00002225218,0.0006062649,0.00002283727,0.0001320835],"category_scores_gemma":[0.00002015783,0.0001189446,0.0000965915,0.001099006,0.0001942749,0.0004409335,0.0002692901,0.0001474826,0.000005066745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002405077,"about_ca_system_score_gemma":0.0002340605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004282419,"about_ca_topic_score_gemma":0.000007344433,"domain_scores_codex":[0.9983888,0.0000107721,0.0002499827,0.0002327488,0.0007271343,0.0003905116],"domain_scores_gemma":[0.9994273,0.000006482615,0.00004245079,0.0003347863,0.00007156957,0.0001174765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004798081,0.00002626933,0.0002582826,0.000007217101,0.000008307728,6.426442e-7,0.001006938,0.9699385,0.008142646,0.009724134,0.01054209,0.0003401591],"study_design_scores_gemma":[0.0001075594,0.00004974478,0.00005540234,0.000002946875,0.00001826702,0.00000165406,0.00006034835,0.9964186,0.001339402,0.001100728,0.0006976723,0.0001477022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3894759,0.0006238006,0.5832563,0.0001109889,0.0003321269,0.0001925487,0.00009767566,0.0002975729,0.02561314],"genre_scores_gemma":[0.9946245,0.000003897919,0.002571544,0.00004254036,0.00003796936,0.00003016049,0.000002730599,0.00001139682,0.002675286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6051486,"threshold_uncertainty_score":0.4850421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02132327985307214,"score_gpt":0.2013223076479598,"score_spread":0.1799990277948877,"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."}}