{"id":"W4232866872","doi":"10.1038/nchembio790","title":"Identifying off-target effects and hidden phenotypes of drugs in human cells","year":2006,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":297,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Drug discovery; Computational biology; Drug action; Biology; Phenotype; Drug; Phenotypic screening; High-content screening; Pharmacology; Bioinformatics; Biochemistry; Gene; Cell","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002392503,0.0001067992,0.0002201598,0.0001049579,0.0000202311,0.00001697901,0.0003793977,0.0002585971,0.000003050453],"category_scores_gemma":[0.00007242746,0.00009638358,0.00004084717,0.0002403803,0.00009561046,0.00009232501,0.0002789272,0.0003266028,0.000001686273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002792907,"about_ca_system_score_gemma":0.0000207004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003170131,"about_ca_topic_score_gemma":0.000002513025,"domain_scores_codex":[0.9990519,0.0001245318,0.0002074446,0.0003376301,0.00009637867,0.000182154],"domain_scores_gemma":[0.9990315,0.0006590043,0.00007730143,0.0001653916,0.00003740003,0.00002936157],"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":[0.000006170653,0.00005096105,0.002323615,0.00005587231,0.000006798707,0.000002917427,0.0001093793,0.00002611769,0.9092684,0.08058674,0.0001504801,0.007412538],"study_design_scores_gemma":[0.000352617,0.00002160028,0.009104806,0.00002247678,0.000002999101,0.000002683556,0.000002814621,0.001783957,0.7554898,0.2328935,0.0002039692,0.0001188175],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874572,0.002018929,0.009420402,0.0001601801,0.0002117486,0.00009610457,0.000003087035,0.00003040392,0.0006019179],"genre_scores_gemma":[0.9384001,0.000003971587,0.06138707,0.0001030268,0.00007172909,0.000003973356,0.00001402136,0.000004526252,0.00001160716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1537787,"threshold_uncertainty_score":0.3930409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006129957830666549,"score_gpt":0.2892791447999085,"score_spread":0.283149186969242,"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."}}