{"id":"W4393029470","doi":"10.36001/phmconf.2014.v6i1.2353","title":"Learning Diagnosis Based on Evolving Fuzzy Finite State Automaton","year":2014,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Fuzzy logic; Fuzzy set operations; Ambiguity; Fuzzy number; Defuzzification; Neuro-fuzzy; Fuzzy set; Event (particle physics); USable; Artificial intelligence; Fuzzy control system; Data mining","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":[0.0004491407,0.0003688109,0.0006690157,0.0005700499,0.0005054804,0.0009549259,0.0009222777,0.0007405049,0.001299299],"category_scores_gemma":[0.002295565,0.0001967754,0.0007401977,0.0003592114,0.0007973155,0.0007764276,0.0006973635,0.000707351,0.0001671775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115363,"about_ca_system_score_gemma":0.0008725234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009882142,"about_ca_topic_score_gemma":0.005791525,"domain_scores_codex":[0.9994197,0.0001027315,0.00004300754,0.000188315,0.0001850471,0.00006126061],"domain_scores_gemma":[0.9992352,0.0003952281,0.00007791852,0.0000741555,0.0001770209,0.00004051622],"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":[0.0001863601,0.00009597042,0.003885417,0.0001135941,0.00007486526,0.0005017784,0.0005185644,0.8458352,0.01370655,0.04091906,0.0006640824,0.09349846],"study_design_scores_gemma":[0.000005109745,0.00002222021,0.0001510425,0.000003549619,0.000007477699,0.00003174827,0.00000960738,0.9945368,0.001173842,0.003779761,0.000273755,0.000005280279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0769999,0.0002245166,0.9174969,0.0002325759,0.00005135482,0.00005521677,0.00007456692,0.0009289424,0.003936084],"genre_scores_gemma":[0.9307494,0.000125291,0.06684922,0.00004791374,0.00001220884,0.00006139364,0.00008673708,0.00001739883,0.002050435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009882142,"threshold_uncertainty_score":0.01964927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239394072242838,"score_gpt":0.2362482723268687,"score_spread":0.2238543316044403,"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."}}