{"id":"W4319003275","doi":"10.3390/pr11020449","title":"Editorial for Special Issue on “Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering”","year":2023,"lang":"en","type":"article","venue":"Processes","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Nuclear power; Energy (signal processing); Systems engineering; Computer science; Power (physics); Engineering management; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007306747,0.0002544785,0.0002355272,0.0001909008,0.0001130045,0.00009274718,0.0001958065,0.0001614992,0.000003042704],"category_scores_gemma":[0.00157399,0.0002480065,0.00001851822,0.0004020581,0.00006299651,0.0003440291,0.00007755987,0.000096255,0.000002611481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000287626,"about_ca_system_score_gemma":0.00003218647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.394754e-7,"about_ca_topic_score_gemma":0.000004079172,"domain_scores_codex":[0.9989922,0.000001510805,0.0001907928,0.0003526959,0.0001188648,0.000343902],"domain_scores_gemma":[0.9992629,0.0002998593,0.00004160441,0.0001549952,0.000195511,0.00004518683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005280811,0.00009081795,0.00002077314,0.02122527,0.0001087711,0.000003502257,0.0008959263,0.004070817,0.005922272,0.004860505,0.5501417,0.4121316],"study_design_scores_gemma":[0.0002540777,0.0002406162,0.000001283419,0.0001748418,0.00001007669,0.000002313272,0.0002103197,0.0009319414,0.04758183,0.006166056,0.9441286,0.0002980882],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02080767,0.04854333,0.7041876,0.004496406,0.1042809,0.007263418,0.003541265,0.1026242,0.004255169],"genre_scores_gemma":[0.3356327,0.1124384,0.3440351,0.0003329875,0.1946009,0.009364209,0.0006960593,0.001829008,0.001070749],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4118335,"threshold_uncertainty_score":0.9999972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008116090285973916,"score_gpt":0.2451569493452665,"score_spread":0.2370408590592926,"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."}}