{"id":"W2887381903","doi":"10.1021/acs.jcim.8b00338","title":"Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images","year":2018,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Sichuan University of Science and Engineering; Data Science Institute, Columbia University; Terry Fox Research Institute","keywords":"Toxicity; Artificial intelligence; Computer science; Deep learning; Chemistry; Organic 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":[0.0007047284,0.00007105665,0.0001819243,0.00009653994,0.00007037573,0.00009161627,0.0002560071,0.00004100151,0.000001085913],"category_scores_gemma":[0.0004989824,0.00004818493,0.00009275846,0.0001382458,0.00007790839,0.001743263,0.0001034898,0.0001539605,9.114321e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001532902,"about_ca_system_score_gemma":0.00004452642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007987143,"about_ca_topic_score_gemma":5.110898e-7,"domain_scores_codex":[0.998899,0.00005727887,0.0006756551,0.00005315353,0.0002282856,0.0000866647],"domain_scores_gemma":[0.9977599,0.0008463014,0.0006425729,0.00008439506,0.0006246099,0.00004217002],"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":[0.0002617519,0.00006080185,0.0005369001,0.00008682481,0.000139426,1.446392e-7,0.01119797,0.8028015,0.1191307,0.002240223,0.0000921071,0.06345171],"study_design_scores_gemma":[0.0002799192,0.00007835551,0.00007339425,0.00005887263,0.00001116702,0.000007787418,0.0002201651,0.908662,0.08693729,0.003542545,0.00008484015,0.00004363127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4914265,0.0000332025,0.5083314,0.0001057234,0.00004548026,0.00003623666,0.000002213704,0.000004265426,0.0000150406],"genre_scores_gemma":[0.8981686,0.00001797208,0.1016358,0.0001131194,0.000058489,9.66161e-7,0.000002586252,0.000002221318,3.116919e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4067421,"threshold_uncertainty_score":0.1964924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05758080478849874,"score_gpt":0.2957700221349007,"score_spread":0.2381892173464019,"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."}}