{"id":"W2057026881","doi":"10.1002/1520-6386(200034)11:4<57::aid-cir9>3.0.co;2-9","title":"Can government CI bolster regional competitiveness?","year":2000,"lang":"en","type":"article","venue":"Competitive Intelligence Review","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture Food and Rural Development","funders":"University of Alberta","keywords":"Government (linguistics); Value (mathematics); Business; Jurisdiction; Corporate governance; Competitive advantage; Resource (disambiguation); Precondition; Private sector; Industrial organization; Marketing; Public relations; Economics; Finance; Economic growth; Political science; Computer science","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":[0.004082496,0.0003929671,0.0005094029,0.002733082,0.00230181,0.01645543,0.001601277,0.003149557,0.01601486],"category_scores_gemma":[0.01259301,0.000292388,0.0005607334,0.005511555,0.006436324,0.009288264,0.005197671,0.002337937,0.003559223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008831,"about_ca_system_score_gemma":0.01078094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02468105,"about_ca_topic_score_gemma":0.0271106,"domain_scores_codex":[0.995884,0.001239981,0.00009058653,0.0003638441,0.0009567913,0.001464835],"domain_scores_gemma":[0.9958422,0.001074189,0.000645698,0.0004358491,0.001216904,0.0007851234],"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":[0.00005785829,0.00004214116,0.009109518,0.0004095944,0.0000596857,0.0005035248,0.003187663,0.002467758,0.0002502576,0.8172054,0.0410982,0.1256083],"study_design_scores_gemma":[0.0000351328,0.0001014329,0.01656392,0.0007217405,0.00008941518,0.0006553191,0.0200793,0.002328659,0.0007568364,0.2374684,0.7211438,0.00005595081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03197555,0.01391191,0.002992963,0.07441538,0.0006372322,0.00002922566,0.0001091528,0.0001902193,0.8757384],"genre_scores_gemma":[0.9441789,0.01422463,0.001661347,0.00793248,0.0008319918,0.00004080509,0.0001124553,0.00007661733,0.03094088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02468105,"threshold_uncertainty_score":0.06407362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03680491966244985,"score_gpt":0.2685407000215753,"score_spread":0.2317357803591255,"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."}}