{"id":"W4236846702","doi":"10.1158/1538-7445.sabcs18-lb-097","title":"Abstract LB-097: Whole transcriptome dose response profiling enables characterization of efficacy, metabolism, side effects and cytotoxicity in a single comprehensive assay","year":2019,"lang":"en","type":"article","venue":"Molecular and Cellular Biology / Genetics","topic":"bioluminescence and chemiluminescence research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transcriptome; Profiling (computer programming); Cytotoxicity; Computational biology; Chemistry; Computer science; Biology; Biochemistry; In vitro; Gene; Gene expression","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002288225,0.001558316,0.002405042,0.001730227,0.000798671,0.002198368,0.001507238,0.001254753,0.01673718],"category_scores_gemma":[0.001402743,0.0009073037,0.001809969,0.001742774,0.000762331,0.001087576,0.001331439,0.003189278,0.01544324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051859,"about_ca_system_score_gemma":0.001394649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002525342,"about_ca_topic_score_gemma":0.003838259,"domain_scores_codex":[0.9972699,0.0003259153,0.0001742911,0.0005236189,0.001531066,0.0001750851],"domain_scores_gemma":[0.9985617,0.0003961609,0.00017084,0.0002757138,0.0005051914,0.00009040198],"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":[0.0005939385,0.0002190935,0.002128581,0.0007806237,0.00009973465,0.0001107632,0.0001161188,0.001633975,0.9291171,0.001269432,0.02630969,0.03762098],"study_design_scores_gemma":[0.00006980221,0.0005912345,0.01207028,0.00009618045,0.0001625756,0.0003737614,0.00007092606,0.01299269,0.8981522,0.001252624,0.07400595,0.0001617784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1129899,0.00329315,0.4953099,0.001055364,0.0007313545,0.001155626,0.2589257,0.08733844,0.03920065],"genre_scores_gemma":[0.2130564,0.003892251,0.4045443,0.002113489,0.0002362166,0.005298433,0.2984413,0.0176913,0.05472634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01673718,"threshold_uncertainty_score":0.05599141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01054556821551011,"score_gpt":0.2475778788480071,"score_spread":0.2370323106324969,"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."}}