{"id":"W4365147995","doi":"10.3390/s23083907","title":"Auto Sizing of CANDU Nuclear Reactor Fuel Channel Flaws from UT Scans","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Power Generation; Dalhousie University","funders":"Ontario Power Generation","keywords":"Sizing; Nuclear power plant; Process (computing); Channel (broadcasting); Nuclear fuel; Nuclear engineering; Spent nuclear fuel; Computer science; Uranium; Engineering; Materials science; Electrical engineering; Chemistry; Nuclear physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001003632,0.000152594,0.0002119985,0.0001356515,0.00002800128,0.00001424416,0.000157773,0.00009398538,0.00003486507],"category_scores_gemma":[0.0001289159,0.0001673539,0.00005665796,0.000318884,0.00004867362,0.00006195894,0.00005028671,0.0001463614,0.0000737642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007767769,"about_ca_system_score_gemma":0.00001139774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00141703,"about_ca_topic_score_gemma":0.0001268849,"domain_scores_codex":[0.9991955,0.00002214696,0.0001943172,0.0001797214,0.0001470315,0.0002612634],"domain_scores_gemma":[0.9994311,0.000129455,0.00004208088,0.0002926053,0.00003801589,0.00006677114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002280084,0.00003087044,0.007289792,0.0003764821,0.0001637504,0.0001464247,0.007794106,0.002051015,0.965167,0.008381374,0.007070214,0.001506179],"study_design_scores_gemma":[0.002139962,0.0003591878,0.2629009,0.002124008,0.0002640428,0.00006323149,0.004678096,0.2878959,0.1945801,0.2253975,0.01574941,0.003847583],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860557,0.00002993239,0.00006235114,0.00004755067,0.0002557276,0.0001130139,0.00007337717,0.003128234,0.01023405],"genre_scores_gemma":[0.9787616,0.00002696258,0.02094853,0.00001028279,0.0001119004,0.000004623244,0.00001337632,0.0000932535,0.0000294435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7705868,"threshold_uncertainty_score":0.6824494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02022748633729184,"score_gpt":0.2269824745027029,"score_spread":0.2067549881654111,"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."}}