{"id":"W2151383084","doi":"10.5267/j.uscm.2015.4.002","title":"Ranking business intelligence factors influencing on development of export","year":2015,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ranking (information retrieval); Business; Business intelligence; Business development; Marketing; Industrial organization; Operations management; Computer science; Knowledge management; Artificial intelligence; Economics","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":[0.001108706,0.0002718738,0.0001503627,0.002134434,0.0004755362,0.001274735,0.0001679233,0.0001696283,0.002292959],"category_scores_gemma":[0.006229127,0.0001033425,0.0002278197,0.001507083,0.0003823422,0.0005634538,0.0006297042,0.0003484137,0.0002434233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005960896,"about_ca_system_score_gemma":0.001127085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002555357,"about_ca_topic_score_gemma":0.004693803,"domain_scores_codex":[0.9992029,0.0001966578,0.00008377108,0.0000586469,0.000296937,0.0001611339],"domain_scores_gemma":[0.9918082,0.002265667,0.002781816,0.0002350855,0.001493101,0.00141615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002383491,0.00007980472,0.9728435,0.00002999675,0.00001474297,0.0002036222,0.0007701283,0.0001706827,0.0003265736,0.000279596,0.0002065186,0.02505091],"study_design_scores_gemma":[0.000001346343,0.00005011406,0.9951168,0.00001830826,0.00001351767,0.0001174114,0.002364246,0.0003601876,0.000326963,0.0001203405,0.001504425,0.000006304072],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931318,0.0001208707,0.0003291337,0.00009790306,0.000004261955,0.00002331515,0.00005133632,0.000007179458,0.006234238],"genre_scores_gemma":[0.9990866,0.0001115594,0.0003777294,0.000006242039,0.000003578558,0.000005623091,0.00006624847,0.000001367686,0.0003409676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002555357,"threshold_uncertainty_score":0.007670701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.088458450951219,"score_gpt":0.2865920840352451,"score_spread":0.1981336330840261,"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."}}