{"id":"W4240633503","doi":"10.21203/rs.2.20017/v1","title":"Genetic profiling of 2,683 Vietnamese genomes from non-invasive prenatal testing data","year":2020,"lang":"en","type":"preprint","venue":"Research Square (Research Square)","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vietnamese; Profiling (computer programming); Computational biology; Biology; Genome; Genetics; Computer science; Gene","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":["metaepi_narrow","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004157943,0.0006734142,0.0008919839,0.0006416321,0.0006929023,0.0004326068,0.004749377,0.0009010085,0.0002150594],"category_scores_gemma":[0.006279273,0.0006792333,0.0002984048,0.001024078,0.0009840853,0.00003404063,0.0187364,0.003066575,0.0001379991],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002535046,"about_ca_system_score_gemma":0.006085086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003875638,"about_ca_topic_score_gemma":0.0004783523,"domain_scores_codex":[0.9891691,0.00210557,0.00120154,0.002735559,0.002879389,0.001908837],"domain_scores_gemma":[0.9897051,0.00120336,0.0003626535,0.004393529,0.003651383,0.0006839771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001061831,0.001277811,0.08762912,0.01306253,0.002017245,0.0005280552,0.005039115,0.005769985,0.8565596,0.0003230977,0.01305059,0.01368104],"study_design_scores_gemma":[0.004223295,0.006116237,0.04308584,0.00585173,0.0002695151,0.00007029845,0.02082414,0.03422035,0.8560017,0.01423584,0.01142017,0.003680865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9732246,0.00922307,0.001375058,0.0006831045,0.0002818733,0.003487059,0.009970638,0.00005967556,0.001694877],"genre_scores_gemma":[0.9649314,0.002403142,0.01938921,0.00002446013,0.002238022,0.0005383595,0.0100149,0.0001767532,0.0002837585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04454328,"threshold_uncertainty_score":0.9995659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1557903199865121,"score_gpt":0.3895504407007536,"score_spread":0.2337601207142415,"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."}}