{"id":"W2006587580","doi":"10.2174/1573409052952288","title":"Inductive Descriptors: 10 Successful Years in QSAR","year":2005,"lang":"en","type":"article","venue":"Current Computer - Aided Drug Design","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Quantitative structure–activity relationship; Electronegativity; Steric effects; Context (archaeology); Substituent; Inductive effect; Biological system; Chemistry; Computational chemistry; Computer science; Artificial intelligence; Machine learning; Stereochemistry; Organic chemistry; Biology","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":[0.001401944,0.0004031953,0.0004432224,0.0006491431,0.0001076213,0.0004265067,0.001921952,0.00008440435,0.0000657357],"category_scores_gemma":[0.00007901658,0.0004358751,0.0001591207,0.001252209,0.00009916133,0.002083011,0.0007552313,0.0005104227,0.0004733891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003881899,"about_ca_system_score_gemma":0.0003662484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000351692,"about_ca_topic_score_gemma":0.0000100393,"domain_scores_codex":[0.9957619,0.001143996,0.0006899904,0.001054205,0.0006831327,0.0006667675],"domain_scores_gemma":[0.9977745,0.0008256751,0.0002161166,0.0007877039,0.0001679207,0.0002280153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003179999,0.0004778796,0.0008305746,0.00002415733,0.00003182119,0.0000349061,0.003516854,0.185153,0.00005270425,0.0119264,0.02087886,0.7770411],"study_design_scores_gemma":[0.001224682,0.00008117568,0.01023621,0.0001662865,0.00001060446,0.00001906234,0.00003065062,0.9418736,0.0009597239,0.01367247,0.03098542,0.0007401062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07609531,0.0006897427,0.9195768,0.0006145141,0.002142165,0.000491526,0.000004230807,0.0002570956,0.0001286781],"genre_scores_gemma":[0.3073435,0.00002858512,0.6909295,0.0003744878,0.001072022,0.00007426687,0.00001561895,0.0000426573,0.0001192973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.776301,"threshold_uncertainty_score":0.9998093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04817321057054227,"score_gpt":0.3089446122647206,"score_spread":0.2607714016941783,"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."}}