{"id":"W2389977909","doi":"","title":"Application of GA-BP Algorithm in the Forecast for the Orthogonal Test","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Artificial neural network; Convergence (economics); Genetic algorithm; Nonlinear system; Rate of convergence; Research Object; Test data; Grafting; Artificial intelligence; Machine learning; Key (lock)","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":[0.0009810658,0.0006598579,0.0006004305,0.0005730272,0.000369398,0.0004909512,0.0006016251,0.0006400339,0.00081875],"category_scores_gemma":[0.002801333,0.0002354176,0.0003985651,0.0005883345,0.0003826926,0.0007034809,0.0003979831,0.0009410743,0.0002155631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005384622,"about_ca_system_score_gemma":0.00116148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01473718,"about_ca_topic_score_gemma":0.008410305,"domain_scores_codex":[0.9996302,0.0001100978,0.00001752891,0.00008411871,0.0001123989,0.00004566865],"domain_scores_gemma":[0.9995284,0.0002341101,0.00004417969,0.0000263342,0.0001486031,0.00001836939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001716686,0.00008930144,0.002980986,0.00007511435,0.00005707154,0.00007771292,0.0000846215,0.7510003,0.007620276,0.006348389,0.001469776,0.2300247],"study_design_scores_gemma":[0.00000378002,0.00001554004,0.0001790737,0.000001730424,0.00000391302,0.000007318478,0.000004441905,0.9980102,0.001008646,0.0005521736,0.0002093311,0.000003904432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0392947,0.0001386746,0.9581888,0.0001186955,0.0000592911,0.00003814455,0.00003568657,0.0005366124,0.001589384],"genre_scores_gemma":[0.706331,0.0002013977,0.2900819,0.00006180123,0.00003140251,0.0001395619,0.0001527927,0.00008518238,0.002915053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01473718,"threshold_uncertainty_score":0.02930284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00403180274854464,"score_gpt":0.2111493409059278,"score_spread":0.2071175381573832,"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."}}