{"id":"W1551227954","doi":"10.5539/ass.v11n20p112","title":"Prospective Mechanisms of Peripheral Areas Investment and Innovation Potential Formation","year":2015,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Peripheral; Business; Political science; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001560142,0.000353869,0.0002219803,0.001524288,0.0007345505,0.004293272,0.000716974,0.0008433504,0.01823035],"category_scores_gemma":[0.00347907,0.0002706234,0.0004469713,0.001015261,0.001694469,0.003046765,0.002083156,0.0008290573,0.001693031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001996759,"about_ca_system_score_gemma":0.001510286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000834776,"about_ca_topic_score_gemma":0.0007073103,"domain_scores_codex":[0.9991431,0.0002037931,0.00004178144,0.000225344,0.0001464298,0.0002395508],"domain_scores_gemma":[0.9982102,0.0005795561,0.0002836883,0.0001844258,0.0003880796,0.0003541014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001370118,0.0001231308,0.0320086,0.0002683051,0.00006363622,0.0005051006,0.002111672,0.006166623,0.006031939,0.8872049,0.00200245,0.06337665],"study_design_scores_gemma":[0.0001397607,0.0004871032,0.1413254,0.0004644874,0.0002098718,0.001367865,0.006073164,0.03668672,0.01229749,0.6841429,0.1167181,0.00008702301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.553563,0.002244649,0.071953,0.003370364,0.00009922664,0.0003002452,0.0005248038,0.0002994157,0.3676454],"genre_scores_gemma":[0.9782549,0.0004176182,0.004531458,0.0000650595,0.00002294667,0.000088793,0.00009205404,0.00001520308,0.01651192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01823035,"threshold_uncertainty_score":0.06098658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02939573009106712,"score_gpt":0.2938296499843441,"score_spread":0.264433919893277,"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."}}