{"id":"W2054153313","doi":"10.1007/s001700170096","title":"Fuzzy Logic Application in Gasket Selection and Sealing Performance","year":2001,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Gasket; Selection (genetic algorithm); Fuzzy logic; Industrial and production engineering; Engineering; Computer science; Engineering drawing; Manufacturing engineering; Mechanical engineering; 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":[0.0006751566,0.0003869403,0.0005911162,0.0008399936,0.0006070281,0.001079764,0.0004479811,0.0008414015,0.002653154],"category_scores_gemma":[0.002023042,0.0002241531,0.0003705704,0.0008171425,0.0003196534,0.000550993,0.0002125626,0.0004193836,0.0003812834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007552307,"about_ca_system_score_gemma":0.0005084477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003921208,"about_ca_topic_score_gemma":0.002919341,"domain_scores_codex":[0.999612,0.00009289086,0.00002406015,0.0000701652,0.0001643103,0.00003653011],"domain_scores_gemma":[0.9992768,0.0003585754,0.00005352692,0.00003704217,0.0002509274,0.00002318239],"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":[0.001636402,0.0002664082,0.003850656,0.0003677566,0.00007492549,0.000439217,0.0002410516,0.4525536,0.1911645,0.01689781,0.001658636,0.3308491],"study_design_scores_gemma":[0.00001976845,0.0001762538,0.001184339,0.00001590511,0.00003934776,0.0000995891,0.00005707919,0.9350456,0.05861659,0.003218057,0.001502874,0.00002463915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2134503,0.001846082,0.7707119,0.0003932015,0.0001916536,0.0000589532,0.0001078613,0.001090769,0.01214924],"genre_scores_gemma":[0.9477371,0.0003441276,0.0486716,0.00004637779,0.00003536459,0.00001456226,0.00003940344,0.00003113423,0.003080286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003921208,"threshold_uncertainty_score":0.008875668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007236458246280618,"score_gpt":0.2319733677729915,"score_spread":0.2247369095267109,"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."}}