{"id":"W2112118673","doi":"10.1016/s1574-0080(04)80018-x","title":"Chapter 61 Knowledge spillovers and the geography of innovation","year":2004,"lang":"en","type":"book-chapter","venue":"Handbook of regional and urban economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":925,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Connaught Fund","keywords":"Economic geography; Knowledge spillover; Production (economics); Function (biology); Endogenous growth theory; Dimension (graph theory); Human capital; Knowledge production; Technological change; Space (punctuation); Urbanization; Economics; Spillover effect; Factors of production; Industrial organization; Knowledge management; Economic growth; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001450719,0.000442264,0.0004903727,0.001017873,0.0007099325,0.002804948,0.0005548077,0.0009842906,0.06161973],"category_scores_gemma":[0.0006174407,0.0002105184,0.0003927239,0.002277632,0.000862801,0.002222133,0.0005313212,0.001281592,0.01211265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001572889,"about_ca_system_score_gemma":0.001419098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004981088,"about_ca_topic_score_gemma":0.007614963,"domain_scores_codex":[0.9999033,0.00001657436,0.00000375617,0.00002135725,0.00004214467,0.00001274848],"domain_scores_gemma":[0.9998478,0.00007350327,0.000009275991,0.00001293281,0.00004097555,0.00001542535],"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":[0.00001039476,0.00004107045,0.0002802587,0.0002980424,0.00001320004,0.00006109589,0.0004076191,0.0008421565,0.0002562172,0.5416453,0.3485804,0.1075643],"study_design_scores_gemma":[0.000002628156,0.000005569274,0.0005602619,0.0002648211,0.000007494041,0.0001089711,0.000141768,0.0001689877,0.0001168318,0.1819355,0.8166822,0.000004968592],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001580289,0.1100528,0.005758071,0.009410547,0.002612087,0.00004036926,0.000701484,0.0001303142,0.8697141],"genre_scores_gemma":[0.03871186,0.143106,0.005288377,0.002454546,0.003338415,0.00007804862,0.0009236327,0.0001412863,0.8059577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06161973,"threshold_uncertainty_score":0.2061386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887040589052877,"score_gpt":0.1810302388835663,"score_spread":0.1521598329930375,"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."}}