{"id":"W4405360332","doi":"10.1115/ipc2024-133038","title":"Matching of Corrosion Features in Multiset Pipeline In-Line Inspection Data Utilizing Relative Point Positions","year":2024,"lang":"en","type":"article","venue":"","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multiset; Pipeline (software); Matching (statistics); Computer science; Point (geometry); Line (geometry); Corrosion; Pipeline transport; Data mining; Artificial intelligence; Mathematics; Engineering; Statistics; Materials science; Combinatorics; Geometry; Programming language; Mechanical engineering; Metallurgy","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":[0.000574601,0.0005882044,0.0006362431,0.002865259,0.0002696989,0.0005355163,0.0009219676,0.0008261014,0.001234775],"category_scores_gemma":[0.002168139,0.0002526616,0.0005759405,0.00160255,0.0002607902,0.0009252509,0.0009324001,0.0004435498,0.0005911114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000359319,"about_ca_system_score_gemma":0.0004024961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003006745,"about_ca_topic_score_gemma":0.003782382,"domain_scores_codex":[0.9990496,0.00007271511,0.00006822164,0.0002654793,0.0004405266,0.0001033801],"domain_scores_gemma":[0.9988376,0.0001743434,0.0002121803,0.0002177932,0.0004998042,0.0000581836],"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":[0.001287866,0.0006370058,0.05983084,0.0004768797,0.0001989139,0.001118428,0.0008339736,0.1644505,0.3437373,0.001394961,0.002897172,0.4231362],"study_design_scores_gemma":[0.00001689773,0.0002685228,0.03700456,0.00001606624,0.00003812373,0.0003401626,0.0002640765,0.8858323,0.0744266,0.0004328645,0.001319714,0.00004010875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7116356,0.0001385541,0.2844803,0.00006056934,0.00006174464,0.0001103368,0.000714678,0.001632503,0.001165648],"genre_scores_gemma":[0.938378,0.00005039424,0.05999788,0.00001342859,0.00000773291,0.00003324207,0.0008805578,0.00004617023,0.0005926043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003006745,"threshold_uncertainty_score":0.005978525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02497361290340625,"score_gpt":0.2921137950310493,"score_spread":0.267140182127643,"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."}}