{"id":"W2130240585","doi":"10.1504/ijtlid.2012.044877","title":"South Africa's national system of innovation and knowledge economy evolution: thinking about 'less favoured regions'","year":2012,"lang":"en","type":"article","venue":"International Journal of Technological Learning Innovation and Development","topic":"Entrepreneurship Studies and Influences","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Science and Technology, Ministry of Science and Technology, India; Universiteit van die Vrystaat; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; International Development Research Centre","keywords":"Inequality; National innovation system; Innovation system; Regional science; National economy; State (computer science); Economic geography; Relation (database); Economic growth; Economy; Economic system; Political science; Geography; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001426016,0.0001186631,0.0001869049,0.001012643,0.0001885098,0.000114373,0.0001953167,0.00009639691,0.00001269308],"category_scores_gemma":[0.0007911718,0.00009477705,0.00002022544,0.00081329,0.0001167135,0.0006876418,0.0002162601,0.0002456086,0.000005844692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001230211,"about_ca_system_score_gemma":0.00006450023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002244362,"about_ca_topic_score_gemma":4.659816e-7,"domain_scores_codex":[0.9985493,0.00001517277,0.0008128313,0.0001234565,0.0003617963,0.0001374796],"domain_scores_gemma":[0.996347,0.00005685517,0.001167767,0.00003720136,0.002382392,0.000008808312],"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":[0.00003004243,0.0000550642,0.2061661,0.00004972341,0.00008145408,0.000001284495,0.0004084709,0.00006823144,0.0001670766,0.7817892,0.0001887506,0.01099455],"study_design_scores_gemma":[0.002317755,0.00007760083,0.468141,0.001205635,0.0000484757,0.0001242257,0.01919808,0.0007662326,0.0008277105,0.02234827,0.4842902,0.0006548968],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9730431,0.0008290552,0.01025099,0.001438573,0.0004177753,0.0001087435,8.268019e-7,0.0000893038,0.01382159],"genre_scores_gemma":[0.9972419,0.00001074215,0.00224803,0.0001467782,0.0002809148,0.000006306181,0.000007787134,0.000005813796,0.00005177107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.759441,"threshold_uncertainty_score":0.3864896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04056764515910044,"score_gpt":0.2579302019205916,"score_spread":0.2173625567614911,"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."}}