{"id":"W1979618713","doi":"10.1016/j.ultras.2013.03.007","title":"Ultrasonic monitoring of erosion/corrosion thinning rates in industrial piping systems","year":2013,"lang":"en","type":"article","venue":"Ultrasonics","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thinning; Piping; Ultrasonic sensor; SIGNAL (programming language); Erosion; Petrochemical; Environmental science; Materials science; Computer science; Acoustics; Geology","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":[0.0003903496,0.0001989389,0.0002154805,0.0004342342,0.0001210315,0.0001715032,0.0003271689,0.0002508209,0.0004896048],"category_scores_gemma":[0.0009577656,0.0001791236,0.000082426,0.000291732,0.0001810865,0.0002713856,0.0001186346,0.000220976,0.00008782802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001552511,"about_ca_system_score_gemma":0.00008865805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006919842,"about_ca_topic_score_gemma":0.0009999083,"domain_scores_codex":[0.9997405,0.00003705313,0.00001535415,0.00003833487,0.0001438096,0.00002488693],"domain_scores_gemma":[0.9993201,0.0003386286,0.0001248968,0.00003515002,0.0001593849,0.00002179409],"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":[0.0006237488,0.00008688176,0.01707699,0.0001025407,0.00001408641,0.00009400028,0.0001890961,0.002175715,0.9387363,0.00009561179,0.00008965944,0.04071526],"study_design_scores_gemma":[0.00002637043,0.0009994984,0.08445021,0.00001207122,0.00005954746,0.0003622324,0.0001391858,0.02615693,0.887149,0.00006483529,0.0005594543,0.00002071523],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914293,0.0003007868,0.007733543,0.000009409315,0.000003953036,0.000007147724,0.00002878704,0.00006497208,0.0004221346],"genre_scores_gemma":[0.99712,0.0001064033,0.002405687,0.000004418217,0.000003409562,0.000003680437,0.00002216514,0.000005885636,0.0003283591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006919842,"threshold_uncertainty_score":0.002064407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02918882960046393,"score_gpt":0.2481130122733128,"score_spread":0.2189241826728489,"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."}}