{"id":"W3188474086","doi":"10.1061/9780784483602.016","title":"Smart and Automated Sewer Pipeline Defect Detection and Classification","year":2021,"lang":"en","type":"article","venue":"Pipelines 2021","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Computer science; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000524146,0.0005937484,0.00068931,0.003609918,0.0002113609,0.000766249,0.0009379283,0.0006977461,0.001650771],"category_scores_gemma":[0.0009420454,0.0002777223,0.000430118,0.0009534296,0.0002284781,0.0006826854,0.0006350768,0.0003356095,0.001149383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004677302,"about_ca_system_score_gemma":0.0004796206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006020704,"about_ca_topic_score_gemma":0.008236686,"domain_scores_codex":[0.9992582,0.000048816,0.00003578049,0.0001962986,0.0003814238,0.00007943238],"domain_scores_gemma":[0.9989574,0.0001239144,0.0001749457,0.0001656809,0.0005259269,0.00005212559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004974126,0.0003908612,0.05447511,0.0002661245,0.00008023531,0.0003634787,0.0002768757,0.03693388,0.1246841,0.0009214675,0.009288802,0.7718217],"study_design_scores_gemma":[0.000035159,0.0002878784,0.08496783,0.0000274738,0.0000433914,0.000357575,0.0002246202,0.8510286,0.05791823,0.000699512,0.00435405,0.00005575956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5674669,0.0003116228,0.4056329,0.0001992994,0.00006809556,0.0006298638,0.002815352,0.01747115,0.00540482],"genre_scores_gemma":[0.8185737,0.0001774005,0.172965,0.00005352785,0.00001791613,0.0001547378,0.002501216,0.0001071778,0.005449226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006020704,"threshold_uncertainty_score":0.01197129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008384120614914104,"score_gpt":0.2217338635164306,"score_spread":0.2133497429015165,"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."}}