{"id":"W3125263113","doi":"10.2139/ssrn.1673492","title":"Knowledge in Cities","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Benchmarking; Metropolitan area; Productivity; Earnings; Regional science; Per capita; Economic geography; Geography; Economic growth; Demographic economics; Business; Economics; Marketing; Sociology; Accounting; Demography","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":[0.001520848,0.0001053615,0.0002767837,0.0003696665,0.00009479591,0.00007146446,0.0002643296,0.00008270579,0.0002516335],"category_scores_gemma":[0.00003842484,0.0001137098,0.0001615501,0.0001790045,0.00004375708,0.0001800252,0.00002754191,0.001474476,0.000427964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000315286,"about_ca_system_score_gemma":0.0003206244,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006905416,"about_ca_topic_score_gemma":0.02655651,"domain_scores_codex":[0.9982021,0.000008540044,0.0004800919,0.0001963373,0.0000184488,0.00109441],"domain_scores_gemma":[0.9995462,0.00002516271,0.0002016039,0.0001441243,0.00002172098,0.00006118389],"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":[0.000005503853,0.00003920353,0.03486228,0.000001216968,0.00004575012,9.596204e-7,0.00008696203,0.00002564687,0.00001933051,0.9624569,0.00005143599,0.002404775],"study_design_scores_gemma":[0.0003589636,0.00004713244,0.007637019,0.000002431267,0.000002929175,0.0000549011,0.000280865,0.001537736,0.000006929092,0.9616655,0.02824228,0.0001633408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9554164,0.003366558,0.001494555,0.001914754,0.0004690082,0.00004345073,0.000005616592,0.000009474637,0.03728012],"genre_scores_gemma":[0.992215,0.003253675,0.00006248129,0.00007139108,0.0003185398,0.000004405673,0.000002426575,0.0000151489,0.004056895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03679858,"threshold_uncertainty_score":0.9912063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416354855718952,"score_gpt":0.2114236491098342,"score_spread":0.1972601005526447,"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."}}