{"id":"W1997680903","doi":"10.1038/nchembio.380","title":"A predictive model for drug bioaccumulation and bioactivity in Caenorhabditis elegans","year":2010,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":191,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Caenorhabditis elegans; Bioaccumulation; Drug; Computational biology; Drug discovery; Biology; Model organism; Chemistry; Ecology; Bioinformatics; Pharmacology; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009650863,0.0008562722,0.001353734,0.0009619967,0.0005607866,0.001180356,0.002429112,0.001868113,0.00290685],"category_scores_gemma":[0.002821459,0.0006374014,0.0008226917,0.0007008744,0.001194922,0.001550568,0.000740986,0.001386812,0.0003985872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001711139,"about_ca_system_score_gemma":0.001520778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02384023,"about_ca_topic_score_gemma":0.0129292,"domain_scores_codex":[0.9997696,0.00005245213,0.00001323292,0.00006219649,0.00005602889,0.00004643227],"domain_scores_gemma":[0.9989758,0.0006383568,0.0001408308,0.00004004384,0.0001576948,0.00004727497],"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":[0.00003004001,0.00002111941,0.0002794506,0.00003659932,0.00001598572,0.00006111825,0.00001453197,0.9847076,0.000763157,0.01157415,0.0003002405,0.002196068],"study_design_scores_gemma":[0.000005787028,0.000007414254,0.00007006375,0.000002688491,0.000008942624,0.000008213456,0.000001768919,0.9967438,0.0001240863,0.002923137,0.0001001109,0.000003976907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3416135,0.002085823,0.6122811,0.004229465,0.0001867541,0.0001627659,0.0017069,0.001236144,0.0364975],"genre_scores_gemma":[0.9776264,0.000631273,0.01009384,0.0002553691,0.00004608397,0.0001673626,0.0002700471,0.00007367808,0.01083606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02384023,"threshold_uncertainty_score":0.04740292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005484639938218681,"score_gpt":0.2603570193798038,"score_spread":0.2548723794415851,"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."}}