{"id":"W3124396621","doi":"","title":"Urban Interactions: Soft Skills Versus Specialization","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Economies of agglomeration; Soft skills; Economic geography; Order (exchange); Distribution (mathematics); Business; Census; Industrial organization; Labour economics; Economics; Economic growth; Sociology; Management; Population","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":[0.0006469912,0.0001289576,0.0002713009,0.0002818368,0.0002033898,0.0001315462,0.0002170344,0.00005566527,0.0002780663],"category_scores_gemma":[0.00008201883,0.0001441218,0.0002353692,0.0002065545,0.00001951433,0.0003675801,0.00001211548,0.0006005199,0.0004395423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009730631,"about_ca_system_score_gemma":0.000191826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001168638,"about_ca_topic_score_gemma":0.0007116231,"domain_scores_codex":[0.9982626,0.00001265824,0.0005439687,0.000235071,0.00003777173,0.0009079264],"domain_scores_gemma":[0.9992896,0.00002909051,0.0004095675,0.0001544579,0.00004218215,0.00007507217],"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":[0.00004547325,0.00008664752,0.002075255,5.104323e-7,0.000143324,9.43322e-7,0.00006790445,0.0002706621,0.000004733537,0.9863474,0.001015508,0.00994165],"study_design_scores_gemma":[0.0009187125,0.0002891272,0.002999766,0.000006213229,0.00001975065,0.00003944333,0.0001500579,0.002736338,0.000007552707,0.8913556,0.1012256,0.0002517761],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4016042,0.02103083,0.3734559,0.03337378,0.00603551,0.0005001731,0.00005905893,0.0001622635,0.1637783],"genre_scores_gemma":[0.9882704,0.005900248,0.00008979929,0.0002910456,0.001010605,0.000001894314,0.00001570744,0.00001389225,0.004406422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5866662,"threshold_uncertainty_score":0.5877115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139749083502864,"score_gpt":0.2252458858651115,"score_spread":0.2112709775148252,"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."}}