{"id":"W2912368193","doi":"10.1093/bioinformatics/btz531","title":"Simultaneous prediction of multiple outcomes using revised stacking algorithms","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"HIV/AIDS drug development and treatment","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Saskatchewan","funders":"Canada Research Chairs","keywords":"Stacking; Computer science; Algorithm; Chemistry","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":[0.0001158818,0.0001321036,0.0003194503,0.0001165086,0.00003612674,0.00001135255,0.00004619819,0.00006675638,0.00006421005],"category_scores_gemma":[0.0001269643,0.00009842079,0.00008380387,0.0001332589,0.00002072515,0.0001328977,0.00003091825,0.00006787707,0.0001043409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001026378,"about_ca_system_score_gemma":0.0000844203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005901027,"about_ca_topic_score_gemma":6.144507e-7,"domain_scores_codex":[0.9989687,0.000007786289,0.0004821535,0.00007794729,0.0002929463,0.0001704378],"domain_scores_gemma":[0.9993063,0.0001209471,0.0001795038,0.0002212632,0.0001040841,0.00006792728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009373678,0.0002474793,0.9685046,0.001127995,0.000415097,0.00001946594,0.004520539,0.0008647316,0.001179433,0.00003463317,0.0003266818,0.02266559],"study_design_scores_gemma":[0.004141869,0.0001609571,0.01269076,0.0004671339,0.0001964561,0.00003540092,0.001187499,0.9723181,0.003419622,0.000006278141,0.005206561,0.0001694219],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917599,0.00005692434,0.004607461,0.0001089572,0.0002698271,0.0008971005,0.00005643507,0.0000919173,0.002151506],"genre_scores_gemma":[0.8902178,0.0000290819,0.1066194,0.00007155621,0.00002766741,0.000003367311,0.0001088326,0.00001608492,0.002906248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9714533,"threshold_uncertainty_score":0.4013483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574649529840671,"score_gpt":0.2706057821646921,"score_spread":0.2448592868662854,"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."}}