{"id":"W2279218329","doi":"10.1115/1.4031772","title":"TRICO II Core Inventory Calculation and its Radiological Consequence Analyses","year":2016,"lang":"en","type":"article","venue":"Journal of Nuclear Engineering and Radiation Science","topic":"Graphite, nuclear technology, radiation studies","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"International Atomic Energy Agency","keywords":"TRIGA; Nuclear engineering; Nuclear reactor core; Radiological weapon; Research reactor; Environmental science; Crash; Nuclear reactor; Computer science; Engineering; Nuclear physics; Physics; Neutron; Radiochemistry; Chemistry","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":[0.0004442431,0.0004991362,0.0002871137,0.001616034,0.0002304085,0.0008353652,0.0004289074,0.0001979098,0.001902948],"category_scores_gemma":[0.001065011,0.0001970266,0.000476483,0.0009674333,0.000155365,0.0003093917,0.0003687329,0.0001681632,0.0003082687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183849,"about_ca_system_score_gemma":0.0005654651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01838852,"about_ca_topic_score_gemma":0.0159685,"domain_scores_codex":[0.9998318,0.00002949274,0.000008836076,0.0000317201,0.00006646151,0.00003166684],"domain_scores_gemma":[0.9995925,0.0001080322,0.00008878043,0.00004252827,0.0001497864,0.00001846258],"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":[0.0004655643,0.00004670872,0.1004535,0.0002362594,0.0001233711,0.0005973638,0.0001275943,0.8218946,0.008227202,0.005857578,0.00165135,0.0603189],"study_design_scores_gemma":[0.00001747244,0.0001182987,0.06226887,0.00005317913,0.0001117514,0.0004631848,0.0002255745,0.9113618,0.01597204,0.001692251,0.007675624,0.00003995709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8541322,0.000614395,0.09741965,0.0001298197,0.00002598698,0.000193955,0.005647474,0.0006722957,0.04116426],"genre_scores_gemma":[0.9809095,0.0002244266,0.01417984,0.00001417791,0.00000337616,0.00003824004,0.001986498,0.00007792729,0.002565976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01838852,"threshold_uncertainty_score":0.03656298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0491420289503948,"score_gpt":0.301776314126652,"score_spread":0.2526342851762571,"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."}}