{"id":"W2174510168","doi":"10.1086/676557","title":"Coagglomeration, Clusters, and the Scale and Composition of Cities","year":2014,"lang":"en","type":"article","venue":"Journal of Political Economy","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Composition (language); Diversity (politics); Economic geography; Feature (linguistics); Scale (ratio); Hierarchical clustering; Polar; Regional science; Geography; Computer science; Cluster analysis; Sociology; Artificial intelligence; Physics; Cartography","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":[0.0006797316,0.00006917638,0.0004442445,0.0001214762,0.00006205271,0.00006454928,0.00008035167,0.00003959738,0.00003700864],"category_scores_gemma":[0.00004160241,0.00005479266,0.000111455,0.00003028304,0.0003542182,0.0001765726,0.00002917199,0.00008227542,0.000004420234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002693979,"about_ca_system_score_gemma":0.00001182606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001972101,"about_ca_topic_score_gemma":0.00001727671,"domain_scores_codex":[0.9990292,0.00002719957,0.0007158797,0.00009261355,0.00001659693,0.0001185158],"domain_scores_gemma":[0.9990823,0.0002146976,0.0004638647,0.00008219635,0.00005760353,0.00009939431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000292557,0.00001317067,0.00815305,0.00001493926,0.00005506555,1.39519e-7,0.00009205904,0.00002990359,0.000002246255,0.9913507,0.00009932749,0.0001601842],"study_design_scores_gemma":[0.001927664,0.0001390334,0.01363644,0.00001925258,0.00004138449,0.00005312355,0.0001969139,0.0340443,0.00006875093,0.9390055,0.01074135,0.0001262701],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8986774,0.00102725,0.01479232,0.03609473,0.000145733,0.00009676864,0.00002600817,0.000002710513,0.04913709],"genre_scores_gemma":[0.9981161,0.00009851125,0.0003948267,0.001160058,0.0001702718,0.000001320234,0.000001417711,0.000004851533,0.00005264771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09943871,"threshold_uncertainty_score":0.223438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180619169110752,"score_gpt":0.1991755422710711,"score_spread":0.1873693505799636,"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."}}