{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009856649,0.000241537,0.0002831389,0.00009539865,0.0002091027,0.00006392329,0.0007230751,0.0001316405,0.0407754],"category_scores_gemma":[0.000203327,0.000220414,0.0001041641,0.0003474321,0.000137989,0.0002843386,0.0005124759,0.0002947591,0.0000914802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004951461,"about_ca_system_score_gemma":0.0001371514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002920151,"about_ca_topic_score_gemma":0.0005505398,"domain_scores_codex":[0.9973384,0.00005383276,0.0004212661,0.0008748003,0.001011293,0.0003004432],"domain_scores_gemma":[0.9984832,0.00008651806,0.0001622268,0.001066247,0.00007983518,0.0001220189],"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":[0.00002561272,0.000399684,0.001056877,0.00005121936,0.0001564795,0.0003047544,0.0002423671,0.00008482543,0.000008269708,0.00006515208,0.8853579,0.1122469],"study_design_scores_gemma":[0.0002087084,0.0001415972,0.004176444,0.000005862385,0.00008018214,0.0001719933,0.0005554428,0.001425205,0.000003077462,0.00002479971,0.9929137,0.0002930117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002872895,0.00009644713,0.002872951,0.001572021,0.001712592,0.003992573,0.007715493,0.0005863845,0.9785786],"genre_scores_gemma":[0.009439967,0.001899499,0.01283362,0.001375795,0.0004651886,0.001123258,0.2681362,0.000367185,0.7043593],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2742194,"threshold_uncertainty_score":0.9601015,"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."}}