{"id":"W4386646868","doi":"10.1109/oceanslimerick52467.2023.10244252","title":"False Plot Identification Using Multi-frame Clustering for Compact HFSWR","year":2023,"lang":"en","type":"article","venue":"","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Identification (biology); Cluster analysis; Frame (networking); Plot (graphics); Computer science; Artificial intelligence; Pattern recognition (psychology); Geology; Remote sensing; Telecommunications; Mathematics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001848102,0.0001587431,0.0001564005,0.0001667444,0.00005913746,0.0000774632,0.0001686944,0.00008044664,0.00002172828],"category_scores_gemma":[0.00004003073,0.00017907,0.00007115776,0.0002770523,0.00001231458,0.0001720499,0.00003287164,0.0001009821,0.0003196392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048675,"about_ca_system_score_gemma":0.000005121709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001517283,"about_ca_topic_score_gemma":0.00001596262,"domain_scores_codex":[0.9991527,0.000007481644,0.0002423196,0.0001632917,0.0001030266,0.0003312233],"domain_scores_gemma":[0.9995329,0.00005860515,0.00002270533,0.0002831192,0.00002888595,0.00007377203],"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":[0.000002991765,0.000007540706,0.00003656704,0.0001082313,0.00003005654,0.000001324282,0.000150857,0.8058583,0.1923084,0.0001009895,0.0006015026,0.0007932336],"study_design_scores_gemma":[0.0002802189,0.000007202013,0.00371872,0.00002470886,0.00001299064,0.000003841859,0.00005258908,0.9839405,0.007905766,0.00004355759,0.003796421,0.0002135291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4583771,0.00003241874,0.53697,0.00004498382,0.0007428337,0.0003197158,0.00001389124,0.003218155,0.0002809604],"genre_scores_gemma":[0.9834334,0.00001155236,0.01577408,0.0000219833,0.000115878,0.00001256768,0.00002179917,0.0001540081,0.000454759],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5250562,"threshold_uncertainty_score":0.7302265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06067595332272538,"score_gpt":0.289622146451141,"score_spread":0.2289461931284156,"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."}}