{"id":"W2579881197","doi":"10.1186/s13059-016-1135-5","title":"Genome Informatics 2016","year":2017,"lang":"en","type":"article","venue":"Genome biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital; Princess Margaret Cancer Centre","funders":"","keywords":"Genome Biology; Biology; Genome; Human genetics; Informatics; Translational bioinformatics; Personal genomics; Computational biology; Genetics; Library science; Genomics; Data science; Evolutionary biology; Gene; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004897605,0.0002159984,0.0002417264,0.00008659055,0.0004344019,0.000108705,0.001180098,0.0003882334,0.0001347063],"category_scores_gemma":[0.0003745566,0.0001748835,0.0001229924,0.00003382157,0.0007014449,0.000009069849,0.0008390928,0.0001621258,0.0006187682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002199879,"about_ca_system_score_gemma":0.0001920026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002518401,"about_ca_topic_score_gemma":0.00002117089,"domain_scores_codex":[0.9984396,0.00004032654,0.0004611321,0.0002426813,0.0001598465,0.0006564293],"domain_scores_gemma":[0.998116,0.00001277316,0.0002554402,0.001187899,0.0001528783,0.0002750714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001167894,0.0000925507,0.005608952,0.0001040714,0.0001930089,0.000004816179,0.000283399,0.00000719048,0.9618174,0.0003348408,0.002276723,0.02916027],"study_design_scores_gemma":[0.0008503873,0.0007562625,0.04923195,0.000006794951,0.00001408512,0.0000223632,0.0001387697,0.00005557909,0.009117203,0.0005074081,0.9389073,0.0003919401],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358836,0.001638824,0.007981227,0.00105562,0.001001052,0.0005853592,0.0002668707,0.00004217018,0.05154524],"genre_scores_gemma":[0.987007,0.002829736,0.003078229,0.0006292038,0.0009506159,0.00002604782,0.000648574,0.00002490396,0.004805716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9527002,"threshold_uncertainty_score":0.7953219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104835138017259,"score_gpt":0.2957872628594092,"score_spread":0.2747389114792366,"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."}}