{"id":"W2051786044","doi":"10.1016/j.bmcl.2011.07.074","title":"Strategies to improve in vivo toxicology outcomes for basic candidate drug molecules","year":2011,"lang":"en","type":"article","venue":"Bioorganic & Medicinal Chemistry Letters","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"AstraZeneca (Canada)","funders":"AstraZeneca","keywords":"Chemistry; Drug; Pharmacology; Drug candidate; Toxicology; Biochemical engineering; Medicine; Engineering","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":[0.001671129,0.0007192012,0.0007437954,0.0005146614,0.0003095389,0.0009325983,0.0007892539,0.0003208356,0.003429009],"category_scores_gemma":[0.003055743,0.0002280233,0.0004910427,0.0003979763,0.0003696624,0.0008507764,0.0009240708,0.0008136565,0.0007078208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004511528,"about_ca_system_score_gemma":0.0008005961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004604893,"about_ca_topic_score_gemma":0.001103184,"domain_scores_codex":[0.9995135,0.0001824776,0.00002622444,0.00006142409,0.0001682891,0.00004817229],"domain_scores_gemma":[0.9989213,0.0004471108,0.0001566394,0.0001924221,0.0002436464,0.00003903401],"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":[0.001451312,0.0008970969,0.004501636,0.0005997675,0.0001644033,0.000175839,0.0001056591,0.1202198,0.6678963,0.01823104,0.002927136,0.18283],"study_design_scores_gemma":[0.0001075375,0.001051618,0.001481161,0.00002391079,0.0001173945,0.0001354785,0.00004803836,0.219347,0.7592375,0.01518752,0.003232645,0.00003032042],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4409642,0.001569451,0.5403213,0.001096142,0.0001072897,0.0003909164,0.0009376847,0.00236831,0.01224473],"genre_scores_gemma":[0.8782538,0.001062762,0.1152716,0.0003002331,0.0000441882,0.0002655449,0.0008274893,0.0002927808,0.003681661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003429009,"threshold_uncertainty_score":0.01147115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01802356494508827,"score_gpt":0.2739586395411226,"score_spread":0.2559350745960343,"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."}}