{"id":"W2916429473","doi":"10.3390/infrastructures4010010","title":"Review on Computer Aided Sewer Pipeline Defect Detection and Condition Assessment","year":2019,"lang":"en","type":"article","venue":"Infrastructures","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Serviceability (structure); Automation; Computer science; Pipeline transport; Construction engineering; Sanitary sewer; Pipeline (software); Systems engineering; Consistency (knowledge bases); Engineering; Risk analysis (engineering); Artificial intelligence; Civil engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001107245,0.00081847,0.001203407,0.003518803,0.0002431234,0.001254141,0.001293783,0.001294636,0.006892536],"category_scores_gemma":[0.002806233,0.00037509,0.0009244662,0.00349572,0.0004329795,0.001540481,0.0005101684,0.0008253322,0.002902178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000474188,"about_ca_system_score_gemma":0.001745321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001856926,"about_ca_topic_score_gemma":0.002008545,"domain_scores_codex":[0.9993706,0.0001208828,0.0001118481,0.0001093813,0.0002510331,0.00003628746],"domain_scores_gemma":[0.9969981,0.001666759,0.0002288152,0.00008751128,0.0009553055,0.0000635414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008636503,0.0000647417,0.0003542266,0.02712047,0.0002020302,0.0002213238,0.00007262117,0.00131627,0.002698139,0.003193405,0.03893717,0.9257333],"study_design_scores_gemma":[0.00001171277,0.0001885978,0.001987232,0.007911195,0.0003459829,0.001515594,0.000083546,0.001108128,0.002056502,0.001743738,0.982998,0.00004979491],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004316184,0.9926701,0.003161781,0.0003823771,0.000552524,0.00001860613,0.00006974972,0.00004358246,0.002669703],"genre_scores_gemma":[0.003222754,0.9912488,0.002928065,0.0003041381,0.0005597672,0.0000221321,0.000190446,0.00001310619,0.001510739],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006892536,"threshold_uncertainty_score":0.02305782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003415197945494812,"score_gpt":0.2332365708591946,"score_spread":0.2298213729136998,"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."}}