{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000209023,0.0001248348,0.0002101685,0.0002463356,0.00003366275,0.00001274608,0.0004487019,0.00007231748,0.00002248314],"category_scores_gemma":[0.0000703859,0.00008970713,0.00005688561,0.0001042354,0.00008451328,0.0002517274,0.0000686705,0.0003572127,0.000001052377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006821199,"about_ca_system_score_gemma":0.000002572794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.13052e-7,"about_ca_topic_score_gemma":5.727156e-7,"domain_scores_codex":[0.9991917,0.00001542459,0.0003877042,0.00008480595,0.0001842429,0.0001361256],"domain_scores_gemma":[0.9994763,0.00008022098,0.0001893169,0.0001429554,0.00009229741,0.00001894327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002797158,0.00001085761,0.0003554954,0.00005641067,0.000336621,0.00001973776,0.0002154542,0.7656167,0.1603251,0.001071251,0.00005609227,0.07190832],"study_design_scores_gemma":[0.0005718241,0.0001219765,0.00544826,0.0001454306,0.00005458207,0.0005481321,0.0001262586,0.0280504,0.9454648,0.01732467,0.002002751,0.0001408586],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852896,0.0009527328,0.01203606,0.0007156003,0.0005685563,0.00004217635,0.000004397315,0.0001075768,0.0002833488],"genre_scores_gemma":[0.9723833,0.003322333,0.0241297,0.00002373034,0.00009328508,0.000001813552,7.215367e-7,0.00001493216,0.00003019087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7851398,"threshold_uncertainty_score":0.365815,"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."}}