{"id":"W2156522000","doi":"10.3386/w9112","title":"From Sectoral to Functional Urban Specialization","year":2002,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Economic geography; Business; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003147346,0.0001556804,0.0001363255,0.001002106,0.0004019502,0.0007909833,0.0003003602,0.0001835333,0.01243177],"category_scores_gemma":[0.001213156,0.000154045,0.0004016897,0.00140447,0.0009082555,0.0005863131,0.001472193,0.000311063,0.001263073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009527708,"about_ca_system_score_gemma":0.0005450617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00291619,"about_ca_topic_score_gemma":0.007443002,"domain_scores_codex":[0.9995168,0.00007001374,0.00001676258,0.0001106881,0.0001002415,0.0001854575],"domain_scores_gemma":[0.9988301,0.0001413978,0.0002239669,0.0002705071,0.0003263003,0.0002076819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005805879,0.0001680143,0.6029465,0.0003515491,0.0001374001,0.0008518333,0.003389734,0.01309018,0.01790164,0.1728317,0.009943021,0.1778079],"study_design_scores_gemma":[0.00003038558,0.0001712626,0.914356,0.00005271622,0.0000411694,0.001290616,0.002473258,0.005226516,0.002463748,0.04185672,0.03201861,0.00001905615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8834828,0.00033592,0.007718199,0.0008732521,0.00001871416,0.00003160584,0.00100711,0.0001396152,0.1063928],"genre_scores_gemma":[0.9964174,0.000119971,0.0004802942,0.00007408686,0.000008589207,0.000005014935,0.0002758163,0.00001539655,0.002603316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01243177,"threshold_uncertainty_score":0.04158843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4477968270865048,"score_gpt":0.4296808560047812,"score_spread":0.01811597108172353,"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."}}