{"id":"W3021764960","doi":"10.1101/2020.04.28.065532","title":"A Bayesian neural network for toxicity prediction","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Prioris.ai (Canada)","funders":"","keywords":"Overfitting; Machine learning; Computer science; Artificial intelligence; Artificial neural network; Hyperparameter; Bayesian probability; Dropout (neural networks); Bayesian network; Flexibility (engineering); Data mining; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002399161,0.0009558125,0.001069864,0.001326451,0.0004324051,0.001044849,0.00136195,0.001668685,0.0040397],"category_scores_gemma":[0.006604212,0.0006229642,0.0008239991,0.000994719,0.0004468786,0.001099574,0.0007246293,0.001959926,0.0007623353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00162213,"about_ca_system_score_gemma":0.001299574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02334479,"about_ca_topic_score_gemma":0.01429342,"domain_scores_codex":[0.9992254,0.0002782869,0.00005495086,0.0001800979,0.0001865784,0.00007483344],"domain_scores_gemma":[0.997833,0.001337461,0.0001457012,0.00005939813,0.0005594839,0.00006502712],"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":[0.0001663775,0.0001036073,0.001994308,0.00007027747,0.00007031333,0.00005083652,0.0000161538,0.9095536,0.0005951681,0.002711165,0.002236808,0.08243125],"study_design_scores_gemma":[0.000003651955,0.000009019474,0.0001171874,0.000008951093,0.000004836602,0.000003793426,0.000001231119,0.9982656,0.00009534603,0.00137008,0.0001174815,0.000002872341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09634306,0.004054146,0.8836546,0.003320349,0.0003495611,0.000199397,0.001518928,0.001683994,0.008875966],"genre_scores_gemma":[0.8567169,0.001511148,0.1294469,0.000763263,0.0002582653,0.0002706589,0.002062452,0.00009493125,0.008875391],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02334479,"threshold_uncertainty_score":0.04641783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412511556241923,"score_gpt":0.2241457893822944,"score_spread":0.2100206738198751,"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."}}