{"id":"W4381620383","doi":"10.1016/j.nima.2023.168477","title":"An integrated online radioassay data storage and analytics tool for nEXO","year":2023,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Radioactive contamination and transfer","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Laurentian University; TRIUMF; Carleton University; Snolab; McGill University","funders":"SLAC National Accelerator Laboratory; Pacific Northwest National Laboratory; Lawrence Livermore National Laboratory; Natural Sciences and Engineering Research Council of Canada; Nuclear Physics; Fonds de recherche du Québec – Nature et technologies; Oak Ridge National Laboratory; National Natural Science Foundation of China; Laboratory Directed Research and Development; Brookhaven National Laboratory; U.S. Department of Energy; Office of Science; Canada First Research Excellence Fund; Russian Foundation for Basic Research; National Science Foundation","keywords":"Computer science; Detector; Analytics; Event (particle physics); Data science; Data mining; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002743403,0.0002209872,0.0003043781,0.0003078654,0.0004328546,0.0002904968,0.0002455981,0.0001329334,0.0001005079],"category_scores_gemma":[0.0001895899,0.0002052552,0.00003584586,0.00124345,0.0002458896,0.0006823122,0.0002261437,0.0004838593,0.00000222292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005263439,"about_ca_system_score_gemma":0.00002266173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003226911,"about_ca_topic_score_gemma":0.0001868198,"domain_scores_codex":[0.9973543,0.0006334001,0.0003048113,0.0007291325,0.0004362553,0.0005421338],"domain_scores_gemma":[0.9991352,0.0002444174,0.00007640955,0.0002975555,0.00004194018,0.000204471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001553457,0.0004770644,0.02411379,0.00003503382,0.0001998687,0.000006590146,0.001245982,0.00006202782,0.1899763,0.0001597264,0.0003221912,0.783246],"study_design_scores_gemma":[0.006774922,0.003040859,0.4672278,0.0001397565,0.000122329,0.000009154621,0.004622247,0.4830699,0.01193689,0.00387316,0.01794965,0.001233318],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952545,0.00001438378,0.003520395,0.0001142638,0.0001715672,0.0006090787,0.0001403597,0.00007121153,0.0001042053],"genre_scores_gemma":[0.9860978,0.0006898427,0.0127654,0.00007639366,0.0000605678,0.0000314298,0.0001538715,0.00004366252,0.00008099573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7820128,"threshold_uncertainty_score":0.8370062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09928869167186549,"score_gpt":0.4126016566722655,"score_spread":0.3133129650004,"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."}}