{"id":"W4385779186","doi":"10.23977/acss.2023.070608","title":"Industry iterative transformation based on big data intelligent platform","year":2023,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Path (computing); Matching (statistics); Artificial intelligence; Data science; Marketing and artificial intelligence; Data mining; Intelligent decision support system","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":[0.002292096,0.0006245479,0.0004945174,0.00419034,0.002461114,0.006416522,0.001666925,0.001142909,0.006865465],"category_scores_gemma":[0.006351831,0.0004617689,0.001198599,0.004350114,0.001658026,0.008496925,0.006324497,0.001414337,0.001722803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002169249,"about_ca_system_score_gemma":0.005482188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006556219,"about_ca_topic_score_gemma":0.004437389,"domain_scores_codex":[0.9969209,0.0006439451,0.0002018088,0.0005516293,0.001317302,0.0003644509],"domain_scores_gemma":[0.9976119,0.0005253942,0.0002363324,0.0006091085,0.0007633349,0.0002539171],"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":[0.0002191388,0.000329269,0.0267607,0.000411473,0.0001610492,0.002196922,0.005624268,0.04582898,0.005895176,0.6504885,0.02242487,0.2396597],"study_design_scores_gemma":[0.00006933765,0.0001274736,0.009791801,0.0002112807,0.0001448291,0.0005915797,0.005997538,0.3497926,0.01018971,0.4769436,0.1459825,0.0001578722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1659412,0.0009386041,0.6172921,0.005724736,0.0005662578,0.001173686,0.001406265,0.003491945,0.2034652],"genre_scores_gemma":[0.8261704,0.0008444188,0.1448718,0.0003659473,0.0001274299,0.0005878028,0.001729898,0.0002336008,0.02506859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006865465,"threshold_uncertainty_score":0.02296728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1023408620755945,"score_gpt":0.3029247231208601,"score_spread":0.2005838610452656,"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."}}