{"id":"W2156812434","doi":"10.1080/00420980410001675832","title":"Clusters from the Inside and Out: Local Dynamics and Global Linkages","year":2004,"lang":"en","type":"article","venue":"Urban Studies","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":566,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Social Innovation; University of Toronto","funders":"","keywords":"Context (archaeology); Cluster (spacecraft); Economic geography; Key (lock); Process (computing); Production (economics); Business; Economic system; Industrial organization; Regional science; Economics; Computer science; Sociology; Geography; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001176823,0.0000701233,0.00009922912,0.000007987566,0.0004809589,0.00004528144,0.00007114853,0.00003514547,0.000001328714],"category_scores_gemma":[0.00009038658,0.000046164,0.00001545009,0.00006650329,0.0008514611,0.00006269832,0.00009636524,0.00004541255,0.00000754854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000114345,"about_ca_system_score_gemma":0.00005510191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00281339,"about_ca_topic_score_gemma":0.03367588,"domain_scores_codex":[0.9995039,0.00003594941,0.0000739849,0.0001117875,0.0001364146,0.0001379668],"domain_scores_gemma":[0.9996975,0.0001614778,0.00002525977,0.00004580224,0.00002866544,0.00004128743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000133941,0.00001746339,0.4775655,0.0000102718,0.0002796574,0.00001189973,0.2157136,0.00001043965,5.653523e-7,0.2380651,0.03589449,0.03241764],"study_design_scores_gemma":[0.000712349,0.00003622613,0.654421,0.000084068,0.00005497826,0.000001608716,0.09893356,0.00002342779,0.000002974242,0.1282866,0.1171628,0.0002803956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8842509,0.0208002,0.0002239095,0.07312669,0.0004694486,0.0001855451,0.00002698874,0.00005498766,0.02086135],"genre_scores_gemma":[0.9937836,0.003610961,0.0001534433,0.001291773,0.0002363982,0.000003391654,0.000002138787,0.00000250931,0.0009158208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1768555,"threshold_uncertainty_score":0.983957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03903083521407463,"score_gpt":0.3258861231011838,"score_spread":0.2868552878871092,"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."}}