{"id":"W3113032643","doi":"10.1002/cpch.90","title":"Multiparametric High‐Content Assays to Measure Cell Health and Oxidative Damage as a Model for Drug‐Induced Liver Injury","year":2020,"lang":"en","type":"article","venue":"Current Protocols in Chemical Biology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"National Institute of General Medical Sciences; National Science Foundation","keywords":"Drug; Oxidative phosphorylation; Liver injury; Measure (data warehouse); Pharmacology; High-content screening; Chemistry; Oxidative damage; Oxidative stress; Medicine; Cell; Biochemistry; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001644909,0.001244907,0.0006562859,0.001520427,0.0006648888,0.0009681765,0.001170848,0.001053264,0.009059125],"category_scores_gemma":[0.001429372,0.0006646924,0.0008719275,0.001117436,0.0005260382,0.0008509661,0.00116361,0.001764257,0.004826274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006353823,"about_ca_system_score_gemma":0.0005730639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006553084,"about_ca_topic_score_gemma":0.001918687,"domain_scores_codex":[0.9976113,0.0006098359,0.0002099778,0.0003569281,0.001059563,0.0001523071],"domain_scores_gemma":[0.9980421,0.0006025872,0.0003137151,0.0003722756,0.0005258416,0.0001433572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002054758,0.0001825594,0.0009996567,0.0002945307,0.00003468095,0.00005605724,0.00005827807,0.0004261179,0.985693,0.0006359454,0.002626322,0.008787438],"study_design_scores_gemma":[0.00003032003,0.0004588696,0.005300989,0.00003929564,0.00005929007,0.0002062175,0.00004388668,0.002121158,0.9787072,0.0004469312,0.01255112,0.00003466283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1765835,0.006047383,0.762085,0.001134305,0.0004873393,0.004008704,0.02181675,0.006238526,0.02159836],"genre_scores_gemma":[0.3790188,0.00776536,0.5190009,0.001380497,0.0002106897,0.01364245,0.03234412,0.001304083,0.04533303],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009059125,"threshold_uncertainty_score":0.0303058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2267319509085478,"score_gpt":0.4228894516493431,"score_spread":0.1961575007407953,"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."}}