{"id":"W3043554932","doi":"10.1140/epja/s10050-020-00141-9","title":"The joint evaluated fission and fusion nuclear data library, JEFF-3.3","year":2020,"lang":"lv","type":"article","venue":"The European Physical Journal A","topic":"Nuclear reactor physics and engineering","field":"Engineering","cited_by":678,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories","funders":"","keywords":"Algorithm; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00444484,0.002140872,0.002084478,0.003909832,0.001396499,0.005316763,0.005103628,0.001663474,0.1232448],"category_scores_gemma":[0.007373074,0.001930333,0.001795318,0.005073344,0.0007578164,0.004073326,0.003333707,0.002298321,0.11822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003217801,"about_ca_system_score_gemma":0.004270906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01906378,"about_ca_topic_score_gemma":0.01892689,"domain_scores_codex":[0.9973162,0.000353926,0.0002678863,0.0003141109,0.001561364,0.0001865598],"domain_scores_gemma":[0.9957575,0.0007430096,0.0002950843,0.001527963,0.001397566,0.0002787434],"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":[0.001455344,0.000141269,0.00267707,0.0009046147,0.0001929067,0.0003610704,0.0001371754,0.007619638,0.006912429,0.01357374,0.9163179,0.04970679],"study_design_scores_gemma":[0.0005181971,0.00009457067,0.002682082,0.0001604938,0.0001007305,0.0003067961,0.00006341821,0.0205056,0.02745326,0.0131738,0.9347541,0.0001869405],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002945193,0.0004959739,0.0747873,0.0006205672,0.0001453935,0.0003859912,0.5972939,0.2575494,0.06577621],"genre_scores_gemma":[0.01803427,0.0004923177,0.04736012,0.0006110303,0.00008403146,0.0008450513,0.8519498,0.05308845,0.02753495],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1232448,"threshold_uncertainty_score":0.4122949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04178666404329182,"score_gpt":0.2188709900492226,"score_spread":0.1770843260059308,"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."}}