{"id":"W4313491368","doi":"10.2172/1846241","title":"Quality Control of and Analysis Enabling Use of MARCUS and MICRE data for Scientific Applications","year":2021,"lang":"en","type":"report","venue":"","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanghai Typhoon Institute; Goddard Space Flight Center; Nanjing University; Brookhaven National Laboratory; Peking University; Chinese Academy of Sciences; McGill University; National Aeronautics and Space Administration; University of Oklahoma; Deutsche Forschungsgemeinschaft","keywords":"Data science; Field (mathematics); Computer science; Quality (philosophy); Scientific literature; Control (management); Management science; Engineering; Artificial intelligence; Epistemology; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006825004,0.00009373316,0.0004184171,0.0001127912,0.00007462287,0.00006959713,0.0001143967,0.00003678599,0.00006151017],"category_scores_gemma":[0.00002480642,0.00008356132,0.00006797005,0.000298566,0.00008691444,0.0001112953,0.0001119555,0.00004911658,1.490242e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005984823,"about_ca_system_score_gemma":0.0002690678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003125493,"about_ca_topic_score_gemma":0.00006397923,"domain_scores_codex":[0.9989856,0.00001834192,0.0004000503,0.0003269479,0.0001659285,0.0001030967],"domain_scores_gemma":[0.9985533,0.0002037995,0.0003041997,0.0005423105,0.0003577645,0.00003866258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002307754,0.00009101137,0.9130852,0.0006540816,0.002630805,8.593418e-8,0.00007301504,0.00001513132,0.009837958,0.0005880433,0.0007566951,0.07224488],"study_design_scores_gemma":[0.002387446,0.0000381281,0.3142834,0.0002091777,0.006175479,0.000001271192,0.0005125474,0.03492903,0.03101479,0.0004165939,0.6089134,0.001118813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7957436,0.001851272,0.1879486,0.00003142937,0.0001067253,0.0009680545,0.01229042,0.00001089773,0.001049039],"genre_scores_gemma":[0.9928638,0.00006467482,0.002695619,0.000001748888,0.00004616713,0.0000437267,0.002936427,0.000005959965,0.001341893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6081566,"threshold_uncertainty_score":0.3407532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1467365020175261,"score_gpt":0.3660744550149451,"score_spread":0.219337952997419,"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."}}