{"id":"W4301848574","doi":"","title":"Asset management for water and sewer networks: the contribution of ASTEE","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"GDG Environnement","funders":"","keywords":"Asset management; Asset (computer security); Business; Environmental science; Computer science; Finance; Computer security","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":[0.00145141,0.001235156,0.001108277,0.001313449,0.0006623839,0.00295581,0.001089541,0.001653819,0.003595119],"category_scores_gemma":[0.00306191,0.0002682827,0.000957372,0.002233656,0.0007411322,0.002733815,0.001750011,0.002028614,0.0006407193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001866574,"about_ca_system_score_gemma":0.002381408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01439868,"about_ca_topic_score_gemma":0.006581,"domain_scores_codex":[0.9992961,0.0002173204,0.00003312794,0.0001361454,0.0002265173,0.00009074411],"domain_scores_gemma":[0.9985719,0.0005812442,0.00005406411,0.0001222169,0.000513288,0.0001572683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001317068,0.0002440426,0.002829735,0.000572218,0.0003041017,0.0003757982,0.0003041025,0.4272378,0.002894057,0.182339,0.06425614,0.3185112],"study_design_scores_gemma":[0.00002562595,0.00006506163,0.001795588,0.000147789,0.0001268634,0.0001928073,0.0002064703,0.7022534,0.002370154,0.1899572,0.1028109,0.00004811212],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0803849,0.1019256,0.6987168,0.04140997,0.004923016,0.0001146706,0.0008572796,0.0003975338,0.07127022],"genre_scores_gemma":[0.7146218,0.07095273,0.1299996,0.001614484,0.005931955,0.00007656922,0.0007086977,0.0004240437,0.07567004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01439868,"threshold_uncertainty_score":0.02862972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007387570414173211,"score_gpt":0.1923185432427633,"score_spread":0.1849309728285901,"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."}}