{"id":"W3203959564","doi":"10.1007/s10928-021-09786-5","title":"Machine learning-guided, big data-enabled, biomarker-based systems pharmacology: modeling the stochasticity of natural history and disease progression","year":2021,"lang":"en","type":"article","venue":"Journal of Pharmacokinetics and Pharmacodynamics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"U.S. Department of Defense","keywords":"Biomarker; Computer science; Systems pharmacology; Biomarker discovery; Bayesian probability; Machine learning; Artificial intelligence; Computational biology; Medicine; Biology; Proteomics; Pharmacology","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":[0.002122853,0.0002580599,0.0003919759,0.0002090976,0.0001601219,0.0001155849,0.0009051554,0.00004330497,0.000008787364],"category_scores_gemma":[0.0002680171,0.0001928303,0.000099078,0.0003209913,0.0001712362,0.0004004629,0.000781521,0.0006762324,2.163413e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131413,"about_ca_system_score_gemma":0.0008193608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270349,"about_ca_topic_score_gemma":5.906546e-7,"domain_scores_codex":[0.9969729,0.0009375006,0.0007871045,0.0003849687,0.0006516834,0.0002658011],"domain_scores_gemma":[0.9971465,0.0008007627,0.0007438789,0.000247625,0.0007067197,0.000354462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003201174,0.0002643001,0.0003479694,0.0003836727,0.0002627911,0.0002533251,0.0001506559,0.9105188,0.05880212,0.0004432536,0.001090262,0.02716273],"study_design_scores_gemma":[0.00203376,0.00005284114,0.00009457739,0.0001076845,0.000362017,0.0002835795,0.00001680774,0.9910479,0.0006165365,0.0002145933,0.004968581,0.0002011618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1078663,0.05431497,0.8322511,0.001691299,0.003466278,0.0002666195,0.00007805228,0.00002510811,0.00004027281],"genre_scores_gemma":[0.9883314,0.002394467,0.008413254,0.0004346065,0.0003369851,0.000004205247,0.00002783192,0.00002275235,0.00003443299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8804651,"threshold_uncertainty_score":0.7863393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07609492127232036,"score_gpt":0.3537515108540866,"score_spread":0.2776565895817662,"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."}}