{"id":"W2519753935","doi":"","title":"The Modern Merits of South Koreas Biopharmaceutical Industry","year":2016,"lang":"en","type":"article","venue":"International Journal of Drug Development and Research","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Revenue; General partnership; Leverage (statistics); Population; Business; Economic growth; Economics; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001184522,0.0006364241,0.0002108977,0.001931193,0.001156321,0.007660106,0.0004711809,0.001478998,0.01120437],"category_scores_gemma":[0.001015122,0.0002816168,0.0003719656,0.00292517,0.001310359,0.007099305,0.002123264,0.002922406,0.002113752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002758113,"about_ca_system_score_gemma":0.004702325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002890958,"about_ca_topic_score_gemma":0.005734385,"domain_scores_codex":[0.9994556,0.0001020902,0.000047999,0.00009213915,0.0001566927,0.0001454145],"domain_scores_gemma":[0.9992095,0.0001433023,0.000104127,0.00002900769,0.000283436,0.0002305341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002053998,0.00009550704,0.006820485,0.006327656,0.00007219865,0.0009195651,0.003253308,0.000291547,0.002948499,0.1410889,0.4397657,0.3982113],"study_design_scores_gemma":[0.000004696195,0.00003054828,0.003099069,0.0007401453,0.00001992006,0.0004854412,0.002116295,0.00003942409,0.0002953972,0.004039106,0.9891143,0.00001568302],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02570246,0.5638456,0.00129567,0.2414243,0.01302792,0.00006696195,0.0005173084,0.0001125083,0.1540073],"genre_scores_gemma":[0.1735139,0.6538001,0.001825966,0.09451085,0.00729614,0.00005783647,0.0009000735,0.0001252592,0.06796987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01120437,"threshold_uncertainty_score":0.03748232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05933183003398243,"score_gpt":0.3936548497210722,"score_spread":0.3343230196870898,"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."}}