{"id":"W2080914508","doi":"10.1007/s10822-009-9291-2","title":"Second-generation de novo design: a view from a medicinal chemist perspective","year":2009,"lang":"en","type":"article","venue":"Journal of Computer-Aided Molecular Design","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"Bundesministerium für Bildung und Forschung","keywords":"Workflow; Computer science; Chemist; Task (project management); Suite; Rank (graph theory); Computational biology; Chemistry; Engineering; Mathematics; Biology; Systems engineering; Database; Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002125782,0.0003218627,0.000547678,0.0002963206,0.0001156294,0.0003563145,0.001226913,0.0001154127,0.00003243973],"category_scores_gemma":[0.0002167984,0.0003055081,0.0002832886,0.000539004,0.0000498419,0.0007010932,0.0001041091,0.00043302,0.000008529264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004801114,"about_ca_system_score_gemma":0.001053296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005894427,"about_ca_topic_score_gemma":6.896972e-7,"domain_scores_codex":[0.9962387,0.001262967,0.0007876475,0.0004603263,0.000870958,0.0003793854],"domain_scores_gemma":[0.9971995,0.0006466463,0.0006297121,0.0004513874,0.0007667927,0.0003059249],"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":[0.0001625588,0.0004317647,0.000003395809,0.0000126578,0.0003153383,0.002145424,0.002246815,0.4753852,0.3986087,0.01976994,0.003982026,0.09693618],"study_design_scores_gemma":[0.001642272,0.001330111,0.0005628059,0.0001747757,0.00008223332,0.001724563,0.00002453938,0.7417217,0.1406117,0.111313,0.0003877457,0.0004244588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01400192,0.001861152,0.9808173,0.002377898,0.0004589002,0.0002492373,0.000001593678,0.00005131657,0.0001806775],"genre_scores_gemma":[0.3126722,0.00002411923,0.6846046,0.002089981,0.0005814398,0.000002841639,0.000001580817,0.00001384408,0.000009408223],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2986703,"threshold_uncertainty_score":0.9999397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03992727108155174,"score_gpt":0.3101269784015619,"score_spread":0.2701997073200102,"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."}}