{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03844272,0.00118281,0.001009987,0.00828749,0.002799683,0.005028609,0.002348104,0.001436291,0.006997276],"category_scores_gemma":[0.05707537,0.000901387,0.0009352356,0.007281774,0.001940683,0.003833775,0.003717261,0.002100777,0.004392918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001499629,"about_ca_system_score_gemma":0.004394531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006251761,"about_ca_topic_score_gemma":0.008548645,"domain_scores_codex":[0.9725413,0.004120479,0.001538728,0.002238227,0.0185103,0.001051032],"domain_scores_gemma":[0.9209339,0.009276201,0.006485362,0.021499,0.0405716,0.001233901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003317062,0.0007974557,0.1399966,0.00177249,0.0005399265,0.001427741,0.003244324,0.007265287,0.3189987,0.04553235,0.1208506,0.3562575],"study_design_scores_gemma":[0.000301566,0.0005484769,0.1272834,0.0003192668,0.0001855373,0.001396254,0.0009210352,0.03156573,0.3954206,0.009768036,0.43189,0.0004001533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1832542,0.001654485,0.6519365,0.004310467,0.001435498,0.004627081,0.04852856,0.03947513,0.06477807],"genre_scores_gemma":[0.3165676,0.0005913583,0.6261551,0.0009186759,0.0006278112,0.002199436,0.03211271,0.008334278,0.01249317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03844272,"threshold_uncertainty_score":0.203307,"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."}}