{"id":"W1980778628","doi":"10.1007/s001700200198","title":"Prediction of Gasket Leakage Rate and Sealing Performance Through Fuzzy Logic","year":2002,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Engineering Structural Analysis Methods","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Gasket; Leakage (economics); Fuzzy logic; Materials science; Engineering; Computer science; Mechanical engineering; Forensic engineering; Composite material; 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":[0.0005295416,0.0004832835,0.0004571464,0.0004850809,0.0003136619,0.0006242034,0.0004109706,0.0006373944,0.000741631],"category_scores_gemma":[0.001611446,0.0002312135,0.0004768637,0.0002530318,0.0002592601,0.0004979228,0.0001393053,0.0003189323,0.0001357589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006135236,"about_ca_system_score_gemma":0.0004316074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008118386,"about_ca_topic_score_gemma":0.005579142,"domain_scores_codex":[0.9998201,0.00003062848,0.00001489226,0.00004948721,0.00006087356,0.00002409667],"domain_scores_gemma":[0.9991298,0.0005421487,0.00009970431,0.00003418321,0.0001718093,0.00002237005],"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":[0.0007245814,0.0001705746,0.01160385,0.00008710194,0.00007333431,0.0001447433,0.00007382213,0.8830805,0.02668805,0.0009033537,0.0003595618,0.07609054],"study_design_scores_gemma":[0.0000062915,0.00005154536,0.001275694,0.000002614087,0.00001251572,0.000008666973,0.000005934756,0.9951307,0.003230787,0.0002400261,0.00002980479,0.000005404941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.687739,0.0002306896,0.3095257,0.0001015716,0.0000401733,0.00003204722,0.0001276716,0.0004793206,0.00172384],"genre_scores_gemma":[0.9911168,0.00003746634,0.008495158,0.000006840067,0.00000421802,0.00000936555,0.00003481865,0.000003515727,0.000291788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008118386,"threshold_uncertainty_score":0.01614225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01838088820871603,"score_gpt":0.2375143541596675,"score_spread":0.2191334659509515,"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."}}