{"id":"W7061880745","doi":"","title":"Sewerage infrastructure: fuzzy techniques to model deterioration and manage failure risk","year":2007,"lang":"en","type":"other","venue":"NPARC","topic":"Advanced Power Generation Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"American Water Works Association Research Foundation","keywords":"Fuzzy logic; Sewerage; Robustness (evolution); Flexibility (engineering); Process (computing); Fuzzy set; Markov process","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001069633,0.0008078527,0.0005753074,0.0007823238,0.0005923099,0.001254302,0.001495647,0.001224287,0.003012658],"category_scores_gemma":[0.002234913,0.0003099845,0.0008865601,0.0008433174,0.0006804671,0.00136769,0.0007258747,0.00140543,0.0003566878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666563,"about_ca_system_score_gemma":0.001452877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03107626,"about_ca_topic_score_gemma":0.02775312,"domain_scores_codex":[0.999676,0.00009643374,0.0000180986,0.00005100491,0.0001241083,0.00003437966],"domain_scores_gemma":[0.9993256,0.000391148,0.0001004014,0.00004061991,0.0001121106,0.0000300769],"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":[0.00001601311,0.00002645864,0.0004825375,0.00002619791,0.00002324846,0.00006984612,0.00008290264,0.9372777,0.0007617538,0.04573948,0.0005884895,0.01490535],"study_design_scores_gemma":[0.000003878598,0.00001218424,0.0001012371,0.000007145544,0.000007739848,0.00002160051,0.00001267716,0.9834177,0.0001424548,0.01527391,0.000992669,0.000006766724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0148522,0.0002236504,0.9780101,0.0002561361,0.00003009328,0.00005455366,0.0001287263,0.0001396611,0.006304921],"genre_scores_gemma":[0.653859,0.0008695355,0.3330629,0.0000938643,0.00007749475,0.0002364738,0.0001828868,0.00006013356,0.01155777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03107626,"threshold_uncertainty_score":0.06179076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004290193744573456,"score_gpt":0.2152268383942952,"score_spread":0.2109366446497217,"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."}}