{"id":"W2023788242","doi":"10.1016/j.nucengdes.2007.06.004","title":"A probabilistic model of wall thinning in CANDU feeders due to flow-accelerated corrosion","year":2007,"lang":"en","type":"article","venue":"Nuclear Engineering and Design","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Atomic Energy (Canada); University of Waterloo","funders":"University Network of Excellence in Nuclear Engineering","keywords":"Thinning; Probabilistic logic; Nuclear engineering; Corrosion; Flow (mathematics); Degradation (telecommunications); Engineering; Structural engineering; Materials science; Forensic engineering; Environmental science; Mechanics; Metallurgy; Physics; Mathematics; Electrical engineering; Statistics","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":[0.002378713,0.001239889,0.001690906,0.001665446,0.0009615958,0.002445549,0.003422142,0.003591907,0.00334994],"category_scores_gemma":[0.005503924,0.001919631,0.001274463,0.001441161,0.00249825,0.002177961,0.0009875995,0.001650259,0.0005668676],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002399975,"about_ca_system_score_gemma":0.001005152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02293266,"about_ca_topic_score_gemma":0.01595503,"domain_scores_codex":[0.9993128,0.0001762482,0.00002865138,0.0001701682,0.0001495254,0.0001626298],"domain_scores_gemma":[0.9971111,0.001501531,0.0005902559,0.0001336586,0.0004250136,0.0002383192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004946872,0.00002234628,0.0007881255,0.00002577348,0.00001445407,0.0001162598,0.00002878364,0.983354,0.001052878,0.01296042,0.0003120226,0.001275597],"study_design_scores_gemma":[0.000008193222,0.00001002024,0.0003780324,0.000003935536,0.00001075524,0.00003169846,0.000007351695,0.9963749,0.0001912752,0.002880558,0.00009125486,0.00001201032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3583828,0.001480983,0.6209022,0.001546407,0.0001738698,0.0001613701,0.0009563859,0.0009809081,0.01541513],"genre_scores_gemma":[0.9701976,0.0006682071,0.01217114,0.00008706718,0.00006914103,0.00007983488,0.0003100448,0.0001270663,0.01628992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9976,"threshold_uncertainty_score":0.04559833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02796328890544024,"score_gpt":0.2201347340515344,"score_spread":0.1921714451460942,"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."}}