{"id":"W2561769473","doi":"10.1680/jinam.16.00017","title":"Principles and guidelines of deterioration modelling for water and waste water assets","year":2016,"lang":"en","type":"article","venue":"Infrastructure Asset Management","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Asset (computer security); Component (thermodynamics); Risk analysis (engineering); Process (computing); Selection (genetic algorithm); Computer science; Hierarchy; Analytic hierarchy process; Asset management; Management science; Operations research; Business; Engineering; Economics","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":[0.0001649132,0.0002041986,0.0002020662,0.0001139863,0.00005727206,0.00004378727,0.00009037158,0.00007663669,0.000009836848],"category_scores_gemma":[0.000005436756,0.0001050026,0.0000337238,0.00002430488,0.00003826884,0.000217327,0.0001079102,0.00004600187,8.807784e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003240156,"about_ca_system_score_gemma":0.000002033664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001790219,"about_ca_topic_score_gemma":0.000002190976,"domain_scores_codex":[0.9989724,0.000008039115,0.0003658607,0.0002172114,0.0001231195,0.0003133971],"domain_scores_gemma":[0.9996263,0.00001565221,0.00003465397,0.0001865793,0.00009031751,0.00004652802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008969341,0.000006619605,0.002744879,0.001479497,0.000386351,0.00001092737,0.0008896587,0.216489,0.629582,0.004224659,0.001680401,0.1424163],"study_design_scores_gemma":[0.002230709,0.0001432969,0.003913356,0.0006062335,0.0001990591,0.00002699585,0.000331139,0.08730303,0.8030534,0.01880764,0.08253743,0.0008476404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7481912,0.00007595654,0.2504827,0.0001484397,0.0004071011,0.0003345599,0.0000167713,0.00006640937,0.0002769399],"genre_scores_gemma":[0.9638911,0.0002111331,0.03547851,0.00002471154,0.0001831614,0.00004134045,0.00001695445,0.00003350916,0.0001195798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2156999,"threshold_uncertainty_score":0.4281881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686802809376185,"score_gpt":0.2332562984028626,"score_spread":0.2163882703091007,"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."}}