{"id":"W4409501000","doi":"10.5006/c2023-19167","title":"Corrosion Scale and Moisture Assessments – an Improvement to On-Stream Inspections for CUI Management","year":2023,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Emissions Reduction Alberta","funders":"","keywords":"Corrosion; Moisture; Scale (ratio); Environmental science; Process engineering; Computer science; Reliability engineering; Materials science; Engineering; Metallurgy; Composite material","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":[0.0008303184,0.00114608,0.0007072118,0.002050174,0.0002698049,0.0009095198,0.001110773,0.0006586284,0.001864201],"category_scores_gemma":[0.001971776,0.0003652415,0.0005092417,0.0006685669,0.0002254841,0.00126679,0.0009727933,0.000645893,0.001022352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003296639,"about_ca_system_score_gemma":0.0004504354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00282592,"about_ca_topic_score_gemma":0.006625852,"domain_scores_codex":[0.9989073,0.0002045726,0.0000643881,0.0002706831,0.0004744646,0.00007862646],"domain_scores_gemma":[0.9982595,0.0002128119,0.0003533787,0.0001906673,0.0008767729,0.0001068332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004251576,0.000694295,0.0679749,0.0005668993,0.0001125788,0.000393452,0.0002721139,0.02195673,0.2965484,0.0007145641,0.003373545,0.6069673],"study_design_scores_gemma":[0.00004240953,0.001417768,0.09503184,0.0001217773,0.0001723066,0.0007731235,0.0006613052,0.7604094,0.1314438,0.000911959,0.008878562,0.0001358619],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2519907,0.0011912,0.7356916,0.0003145427,0.0002189944,0.0004690143,0.0005080199,0.004471242,0.005144739],"genre_scores_gemma":[0.7919524,0.0004554525,0.2047581,0.00007109345,0.00005786713,0.00006379642,0.0002867111,0.00008844307,0.002266047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00282592,"threshold_uncertainty_score":0.006236374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296212535809403,"score_gpt":0.2952306441681912,"score_spread":0.2722685188100972,"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."}}