{"id":"W2995108027","doi":"10.18280/ria.330503","title":"An Automobile Noise Prediction Model Based on Extension Data Mining Algorithm","year":2019,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Vehicle Noise and Vibration Control","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Entropy (arrow of time); Noise (video); Data mining; Decision tree; Automotive industry; Artificial intelligence; Principle of maximum entropy; Autocorrelation; Logistic regression; Extension (predicate logic); Algorithm; Machine learning; Pattern recognition (psychology); Engineering; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001237194,0.0007696794,0.001163155,0.001308563,0.0004183169,0.0006688888,0.001282092,0.0008096498,0.0008125943],"category_scores_gemma":[0.002194222,0.000330715,0.00102167,0.001067485,0.0003360478,0.001059807,0.000668767,0.0007514538,0.0002372936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005476633,"about_ca_system_score_gemma":0.0009050951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008173224,"about_ca_topic_score_gemma":0.004750601,"domain_scores_codex":[0.9993992,0.0001108422,0.00004901351,0.0002208626,0.0001579206,0.00006222299],"domain_scores_gemma":[0.999157,0.0004113874,0.00009255312,0.0000392111,0.0002686299,0.00003133489],"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":[0.0001395555,0.0001336147,0.0118073,0.00008360414,0.0001004485,0.0001729794,0.0001018813,0.8792008,0.001843468,0.003532592,0.001197502,0.1016864],"study_design_scores_gemma":[0.000002905205,0.00001374741,0.0004337334,0.000004017815,0.000008314782,0.0000172671,0.000003751914,0.998557,0.0001381302,0.0006779109,0.0001395597,0.00000367649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1314164,0.0008252928,0.8641604,0.0003502022,0.00007196612,0.0001154435,0.0002755173,0.0006322316,0.002152525],"genre_scores_gemma":[0.9035173,0.0005405533,0.09207048,0.0001174327,0.00006572637,0.000258481,0.0004953319,0.00003550332,0.002899319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008173224,"threshold_uncertainty_score":0.01625133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03496262948036433,"score_gpt":0.265192592063113,"score_spread":0.2302299625827486,"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."}}