{"id":"W2955023428","doi":"10.1158/1538-7445.am2019-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":"Cancer Research","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transcriptome; Computational biology; Fold change; Gene expression profiling; Computer science; Benchmark (surveying); Gene expression; Bioinformatics; Biology; Gene; Data mining; Genetics","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":[0.002078036,0.001316749,0.002024778,0.001490857,0.0007105024,0.002078631,0.00119051,0.001178314,0.009485883],"category_scores_gemma":[0.00122474,0.0007090292,0.001590802,0.001482667,0.0007225089,0.0008631891,0.001212204,0.002894707,0.00907089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000999896,"about_ca_system_score_gemma":0.001211389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273814,"about_ca_topic_score_gemma":0.003676355,"domain_scores_codex":[0.9974483,0.0003341429,0.0001521754,0.0004464944,0.001446962,0.0001718892],"domain_scores_gemma":[0.9984809,0.0003669137,0.0001839677,0.0003007268,0.0005651949,0.0001023123],"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":[0.0002614332,0.0001287416,0.001194457,0.0003030366,0.0000520083,0.00005974153,0.00004693776,0.0009596671,0.9759523,0.0005296329,0.006383035,0.01412907],"study_design_scores_gemma":[0.00003818134,0.0005265996,0.0105956,0.00006795716,0.0001249929,0.0002860148,0.00006046898,0.0100335,0.9450679,0.0007207906,0.03236509,0.0001129085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2460597,0.004853386,0.4801891,0.001375218,0.0007592175,0.001171421,0.1864916,0.04461335,0.03448686],"genre_scores_gemma":[0.3915615,0.004508025,0.3503376,0.002264534,0.0002201629,0.003832184,0.1935146,0.009954783,0.04380651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009485883,"threshold_uncertainty_score":0.03173339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06381781574264134,"score_gpt":0.3779032728998042,"score_spread":0.3140854571571629,"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."}}