{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008722362,0.0001253547,0.0002001684,0.0001151905,0.00003910776,0.00000493397,0.0001440407,0.0003488333,0.00003617539],"category_scores_gemma":[0.00013138,0.0001238706,0.0000699273,0.000192815,0.00003117615,0.00004905438,0.000006593121,0.0002779909,0.00002750521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008285286,"about_ca_system_score_gemma":0.00001537379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003050893,"about_ca_topic_score_gemma":0.00001611618,"domain_scores_codex":[0.9991225,0.00002709215,0.0003261648,0.0001488835,0.0001504791,0.0002248915],"domain_scores_gemma":[0.9993497,0.0001450987,0.00004862872,0.0003629868,0.00005545451,0.00003813698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000708109,0.0003719588,0.002009208,0.0004874957,0.0001666826,0.00003446494,0.0005673157,0.09103311,0.6881489,0.1188787,0.0009202904,0.09667376],"study_design_scores_gemma":[0.003708405,0.0003641571,0.00952714,0.000195051,0.00006708359,0.000004813538,0.0002075163,0.181079,0.7942766,0.0056068,0.004405105,0.0005584031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8604085,0.000086001,0.1077978,0.0001123634,0.001170992,0.0005298309,0.000008099667,0.000781198,0.02910522],"genre_scores_gemma":[0.9994258,0.000001715369,0.0003258927,0.00004618629,0.0001211494,0.00001155766,0.000004262391,0.00001994857,0.0000434364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1390173,"threshold_uncertainty_score":0.5051298,"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."}}