{"id":"W1985965486","doi":"10.5539/mas.v4n1p68","title":"Research on Evaluation of Technological Innovation Ability about Guangxi Non-Ferrous Metal Industry based on RBF Neural Network","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disadvantage; Artificial neural network; Ferrous; Business; Computer science; Manufacturing engineering; Artificial intelligence; Metallurgy; Materials science; Engineering","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":[0.001327758,0.0002965785,0.0003151775,0.001436299,0.0001990225,0.0006948456,0.000301847,0.0003821389,0.001362771],"category_scores_gemma":[0.002531677,0.00007601305,0.0003563824,0.001222461,0.0002376851,0.001342128,0.0003003869,0.0002440792,0.0001143798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006543853,"about_ca_system_score_gemma":0.0004380034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006248574,"about_ca_topic_score_gemma":0.004162323,"domain_scores_codex":[0.9994184,0.0001426575,0.00004934958,0.00008272882,0.0002412484,0.00006562976],"domain_scores_gemma":[0.9987203,0.0005213119,0.0002223284,0.00005133367,0.0004168599,0.00006803136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001070611,0.0003662522,0.4575637,0.000729244,0.0005259867,0.0007827886,0.001828247,0.1219841,0.03925977,0.01390607,0.001461236,0.3605219],"study_design_scores_gemma":[0.00005502033,0.0006299745,0.4873611,0.00006807762,0.0002306328,0.0002702035,0.001228532,0.4853094,0.0186986,0.004061631,0.002025952,0.00006092385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709733,0.0003283228,0.02240823,0.000176824,0.000009915397,0.00002177452,0.00008943717,0.00004724533,0.005944939],"genre_scores_gemma":[0.9974482,0.0001346112,0.001749619,0.000006801275,0.000004809772,0.000007526357,0.00005130937,0.000002170106,0.0005949835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006248574,"threshold_uncertainty_score":0.01242441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09279637503944815,"score_gpt":0.3462156875787502,"score_spread":0.253419312539302,"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."}}