{"id":"W3022066516","doi":"10.48550/arxiv.2005.05009","title":"Digit analysis for Covid-19 reported data","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Benford’s Law and Fraud Detection","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Numerical digit; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Virology; Mathematics; Arithmetic; Pathology; Outbreak","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004173587,0.0003750199,0.0005038679,0.009092037,0.0006633432,0.001712183,0.0008860129,0.0005148157,0.02907732],"category_scores_gemma":[0.03583791,0.0001340842,0.0006819863,0.008646397,0.0004012228,0.0008139593,0.001456329,0.001018828,0.007677306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073119,"about_ca_system_score_gemma":0.0007344899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00506645,"about_ca_topic_score_gemma":0.002663663,"domain_scores_codex":[0.9930501,0.001884294,0.0007618042,0.001167476,0.002208606,0.0009276749],"domain_scores_gemma":[0.9714127,0.01415857,0.004350325,0.005589653,0.004070606,0.000418112],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001450591,0.0002572839,0.6458055,0.001040207,0.0007646931,0.0008259839,0.001072001,0.006427548,0.0021645,0.04919236,0.1056599,0.1853393],"study_design_scores_gemma":[0.0001013775,0.0004127194,0.6466678,0.0002892164,0.0002684538,0.001717578,0.002613078,0.04686917,0.007562864,0.02695968,0.2664322,0.0001059112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6030089,0.001609294,0.0487136,0.001450133,0.0008590953,0.0006212266,0.2605805,0.002128085,0.08102925],"genre_scores_gemma":[0.8792931,0.0003542922,0.012349,0.0002234195,0.0001695735,0.0004969387,0.09321845,0.0002013695,0.01369377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9994852,"threshold_uncertainty_score":0.09727335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5332618221046435,"score_gpt":0.3010686252733096,"score_spread":0.2321931968313338,"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."}}