{"id":"W4283021641","doi":"10.2172/1872378","title":"United States Nuclear Data Program Annual Report for FY2021","year":2022,"lang":"en","type":"report","venue":"","topic":"Radioactive contamination and transfer","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Oak Ridge National Laboratory; Brookhaven National Laboratory; U.S. Department of Energy; Argonne National Laboratory; Lawrence Livermore National Laboratory; Nuclear Physics; McMaster University; National Institute of Standards and Technology; College of Engineering, Michigan State University; Office of Science; North Carolina State University; Los Alamos National Laboratory; National Nuclear Security Administration; Michigan State University","keywords":"Staffing; Nuclear data; Fiscal year; Work (physics); Leverage (statistics); Plan (archaeology); Engineering; Political science; Business; Computer science; Nuclear physics; Physics; Finance; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004645392,0.001387512,0.0006453552,0.003480774,0.001389836,0.003340492,0.001900605,0.001494528,0.07204583],"category_scores_gemma":[0.006832201,0.0006277604,0.000555955,0.005391636,0.0002572317,0.002366808,0.001150545,0.001867081,0.06262649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005991733,"about_ca_system_score_gemma":0.02018832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1663122,"about_ca_topic_score_gemma":0.1345882,"domain_scores_codex":[0.9965546,0.0002630559,0.0001452167,0.0002164625,0.002572423,0.0002482699],"domain_scores_gemma":[0.9949625,0.0002862068,0.0002406657,0.0002530745,0.004030186,0.0002273884],"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":[0.00003270842,0.00003318449,0.000370965,0.00009853266,0.000006304283,0.00001306097,0.00001194622,0.0001399809,0.00008921971,0.001751539,0.9854527,0.0119997],"study_design_scores_gemma":[0.00001073103,0.0000118496,0.001463788,0.00008225533,0.000006001717,0.00001058157,0.00003376283,0.00006426906,0.0002004179,0.0004112947,0.997696,0.000008902318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001213302,0.002251577,0.001856444,0.004760985,0.002430984,0.0009199396,0.623867,0.001391283,0.3613085],"genre_scores_gemma":[0.008122951,0.007263745,0.009271791,0.002573,0.0005149399,0.002582791,0.6735473,0.0009449653,0.2951785],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1663122,"threshold_uncertainty_score":0.3306884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05411348437151282,"score_gpt":0.3338224181616115,"score_spread":0.2797089337900987,"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."}}