{"id":"W2059255071","doi":"10.2174/138620706775541828","title":"Interactive Tools for Risk Reduction and Efficiency Improvements in Medicinal Chemistry","year":2006,"lang":"en","type":"article","venue":"Combinatorial Chemistry & High Throughput Screening","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Computer science; Quality (philosophy); Reduction (mathematics); Process (computing); Risk analysis (engineering); Intellectual property; Cluster analysis; Property (philosophy); Data science; Machine learning; Business","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":[0.006714518,0.003080949,0.00112695,0.002851081,0.0006468488,0.002851241,0.00322897,0.001933595,0.03635708],"category_scores_gemma":[0.02763794,0.001199111,0.001113668,0.001972288,0.0009738972,0.003867899,0.003909095,0.002623345,0.006909441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008723639,"about_ca_system_score_gemma":0.000936504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007859992,"about_ca_topic_score_gemma":0.001162727,"domain_scores_codex":[0.9958267,0.002013128,0.0002559306,0.0003325388,0.001418025,0.0001536678],"domain_scores_gemma":[0.9696615,0.02567597,0.0007080396,0.002224191,0.001242076,0.0004882531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002440378,0.0008724475,0.001998703,0.001731156,0.0002632475,0.0007089482,0.001320493,0.04320753,0.02203902,0.03848673,0.1139583,0.7729731],"study_design_scores_gemma":[0.001990051,0.0008099297,0.002789001,0.0008356915,0.0003748366,0.00115716,0.0003198949,0.4552288,0.05806006,0.1791141,0.2988417,0.0004787944],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006127886,0.000771229,0.8744794,0.001071266,0.000111254,0.0003915186,0.001438484,0.1078616,0.007747302],"genre_scores_gemma":[0.07327824,0.0009591703,0.9104709,0.0005774126,0.0001796447,0.001464082,0.001861019,0.006082814,0.005126881],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03635708,"threshold_uncertainty_score":0.1216266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01328274346505063,"score_gpt":0.279148173719607,"score_spread":0.2658654302545563,"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."}}