{"id":"W2064005391","doi":"10.1016/j.nucengdes.2008.07.016","title":"A statistical approach to the prediction of pressure tube fracture toughness","year":2008,"lang":"en","type":"article","venue":"Nuclear Engineering and Design","topic":"Nuclear Materials and Properties","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Atomic Energy (Canada); University of Waterloo","funders":"","keywords":"Fracture toughness; Materials science; Pressure vessel; Toughness; Fracture (geology); Composite material; Structural engineering; Nuclear engineering; Forensic engineering; Engineering","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":[0.0001729108,0.00008417781,0.0001264084,0.00002082252,0.00009389413,0.00003611519,0.0001011719,0.00004970206,0.0001076917],"category_scores_gemma":[0.00004933116,0.00005342885,0.00001245307,0.00004522103,0.00003949017,0.00006219801,0.00003436381,0.00005899734,0.00002716351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003911113,"about_ca_system_score_gemma":0.000007925797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000262353,"about_ca_topic_score_gemma":3.573666e-8,"domain_scores_codex":[0.9994463,0.00003979458,0.0001191556,0.000137796,0.0001304775,0.0001265218],"domain_scores_gemma":[0.9997269,0.00003809151,0.00001934129,0.0001390121,0.00002439348,0.00005224105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002279146,0.00007365773,0.00002480773,0.0002244273,0.00002542598,0.000004485129,0.005340372,0.1481835,0.8204829,0.003290151,0.02174521,0.0003772477],"study_design_scores_gemma":[0.001219781,0.001301246,0.04138663,0.00020203,0.0001728006,0.0004280746,0.0005675057,0.2937017,0.1571748,0.0002302883,0.5027216,0.0008934574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7895097,0.000401601,0.2079829,0.0002339065,0.0004564479,0.0004721695,0.0001038028,0.0002492612,0.0005902313],"genre_scores_gemma":[0.9762858,0.00001785708,0.02345008,0.00007654507,0.00009299869,0.000007350525,0.000001246893,0.00002048169,0.00004760158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.663308,"threshold_uncertainty_score":0.2178765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212773572068602,"score_gpt":0.1896718617515235,"score_spread":0.1675441260308375,"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."}}