{"id":"W1976296737","doi":"10.1068/a35290","title":"Network Structure of an Industrial Cluster: Electronics in Toronto","year":2003,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Economic geography; Cluster (spacecraft); Industrial organization; Resource (disambiguation); Variety (cybernetics); Business; Sample (material); Electronics; Regional science; Resource dependence theory; Economics; Computer science; Geography; Engineering; Management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000223063,0.0001238012,0.0001643192,0.001857444,0.001742438,0.001798883,0.0004454133,0.0002967768,0.007806845],"category_scores_gemma":[0.002352763,0.0001535729,0.0001299195,0.00454556,0.001197338,0.0006308044,0.001323524,0.0001852946,0.0004205941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01303364,"about_ca_system_score_gemma":0.004642915,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8178375,"about_ca_topic_score_gemma":0.8841113,"domain_scores_codex":[0.9996831,0.00006036209,0.00001222986,0.00006921868,0.00006079747,0.0001142065],"domain_scores_gemma":[0.998745,0.0002272405,0.0003101434,0.0000583153,0.0003095285,0.0003497487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004483452,0.0000889154,0.7759573,0.0003222553,0.0001073648,0.001717,0.03377451,0.02858948,0.002321971,0.08802171,0.02146177,0.04718927],"study_design_scores_gemma":[0.00003185162,0.00006312897,0.9146071,0.0001001412,0.00006023062,0.0002769977,0.02974174,0.02102438,0.0006535693,0.004695495,0.02870496,0.0000403401],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728115,0.0003931107,0.0009922391,0.0005923196,0.000006909178,0.00004876692,0.001371498,0.00002717614,0.0237564],"genre_scores_gemma":[0.9959599,0.0001549779,0.0002867392,0.00001016431,0.000002006812,0.000007877965,0.0004292126,0.000002928855,0.003146117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1821625,"threshold_uncertainty_score":0.3664705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500659640820076,"score_gpt":0.1857745510502046,"score_spread":0.1707679546420039,"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."}}