{"id":"W2380617753","doi":"","title":"Reliability Allocation of Crank Mechanism Based on GA","year":2007,"lang":"en","type":"article","venue":"Neiranji gongcheng","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Reliability (semiconductor); Crank; Constraint (computer-aided design); Function (biology); Mathematical optimization; Mechanism (biology); Genetic algorithm; Reliability engineering; Computer science; Production (economics); Engineering; Mathematics; Economics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005545637,0.0007299804,0.0008929014,0.0009050312,0.0004167326,0.0006868136,0.001185113,0.0006488582,0.001423546],"category_scores_gemma":[0.001027695,0.000518513,0.0007484818,0.0007761303,0.0005567707,0.0007415451,0.0004393566,0.0005315092,0.0001709225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002161,"about_ca_system_score_gemma":0.001264162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009814015,"about_ca_topic_score_gemma":0.004785346,"domain_scores_codex":[0.9996048,0.0001111686,0.00001487489,0.00008701387,0.0001132898,0.00006885885],"domain_scores_gemma":[0.9997531,0.00008271675,0.00003309783,0.00003347207,0.00008337379,0.00001418568],"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":[0.00002452597,0.000008694625,0.0002177059,0.00003454486,0.00001159196,0.00002543821,0.00001931146,0.9835721,0.001485423,0.004069561,0.0001914132,0.01033972],"study_design_scores_gemma":[0.000007819947,0.00001772767,0.0001223232,0.000004333243,0.000007801415,0.00001340429,0.0000057036,0.9976571,0.0004387368,0.00144351,0.0002759841,0.000005664797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1010793,0.0007205238,0.8877234,0.0001195809,0.00004847595,0.00008841569,0.00005078976,0.0005568541,0.009612634],"genre_scores_gemma":[0.9280897,0.0005129757,0.06779388,0.00002357391,0.00001432457,0.0001158426,0.00005503234,0.0000577047,0.003336884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009814015,"threshold_uncertainty_score":0.01951379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009649742678582736,"score_gpt":0.2076047953506461,"score_spread":0.1979550526720634,"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."}}