{"id":"W2060136803","doi":"10.1007/s11365-008-0080-5","title":"The next Silicon Valley? On the relationship between geographical clustering and public policy","year":2008,"lang":"en","type":"article","venue":"International Entrepreneurship and Management Journal","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Silicon valley; Cluster analysis; Regional policy; Public policy; Cluster (spacecraft); Entrepreneurship; Economic geography; Regional science; Range (aeronautics); Political science; Geography; Business; Economics; Economic growth; Computer science; Engineering","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":[0.004329021,0.0001632921,0.0005140082,0.00122442,0.002025298,0.004763894,0.0008080343,0.002075032,0.010917],"category_scores_gemma":[0.01759513,0.0001880965,0.0003769008,0.002875597,0.005673232,0.004727512,0.002254582,0.002238133,0.0002505164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004944998,"about_ca_system_score_gemma":0.004225675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03631416,"about_ca_topic_score_gemma":0.03455177,"domain_scores_codex":[0.9982131,0.001124711,0.00003563357,0.0001918245,0.0001173155,0.0003175214],"domain_scores_gemma":[0.9699696,0.02403039,0.003006312,0.0005067119,0.001351637,0.00113524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002054721,0.0001434306,0.05134283,0.0001871708,0.0001214996,0.0003953596,0.003097121,0.01270854,0.0001129896,0.8910711,0.01640712,0.02420748],"study_design_scores_gemma":[0.0001395704,0.0001897603,0.07661837,0.0008274823,0.0002728114,0.0002468951,0.04726717,0.02816481,0.0004580109,0.8087143,0.03698484,0.0001159831],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6356111,0.006224259,0.004980045,0.239946,0.0001519865,0.0000431244,0.0002928004,0.00004231204,0.1127083],"genre_scores_gemma":[0.995585,0.001546973,0.0002842081,0.001663138,0.00006192607,0.00001186835,0.00002670855,0.000005576185,0.0008145772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03631416,"threshold_uncertainty_score":0.0722056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09274651472454296,"score_gpt":0.2523762579670956,"score_spread":0.1596297432425526,"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."}}