{"id":"W4386768155","doi":"10.2139/ssrn.4564571","title":"An Improved Algorithm of Module Data Reconciliation for Nuclear Power Plant System","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Nuclear power plant; Computer science; Algorithm; Nuclear engineering; Engineering; Physics; Nuclear physics","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":[0.00100672,0.001045288,0.001281935,0.002205191,0.001147973,0.001480469,0.001666479,0.0008215984,0.004675796],"category_scores_gemma":[0.003018334,0.0004634119,0.0008564786,0.001872453,0.0003619229,0.00144047,0.001643438,0.000853207,0.001844988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005807976,"about_ca_system_score_gemma":0.001568364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004051753,"about_ca_topic_score_gemma":0.003564566,"domain_scores_codex":[0.9988734,0.0002473076,0.00009652739,0.0003258837,0.0003071501,0.0001497223],"domain_scores_gemma":[0.9988959,0.0001983777,0.00007849572,0.0004083838,0.0003864192,0.00003245068],"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":[0.000739787,0.0001192858,0.002611105,0.0002115603,0.0001615245,0.0001804846,0.0002100436,0.06921674,0.019173,0.0062152,0.01045078,0.8907106],"study_design_scores_gemma":[0.0001525559,0.0001944916,0.003257652,0.0000245192,0.000118432,0.0003542754,0.0001081654,0.9344687,0.03575385,0.01151705,0.01397596,0.00007436305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01926382,0.0003000195,0.9715828,0.00009739482,0.000118438,0.00009856816,0.0003604755,0.00706073,0.001117861],"genre_scores_gemma":[0.2257905,0.0001065702,0.7688807,0.0001170156,0.0000828139,0.0001644034,0.00177446,0.0006015183,0.002481983],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004675796,"threshold_uncertainty_score":0.01564211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657176513741709,"score_gpt":0.2377567263096942,"score_spread":0.2211849611722772,"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."}}