{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008026902,0.001675499,0.002021132,0.002374331,0.000431107,0.002441881,0.001604118,0.001542874,0.002951831],"category_scores_gemma":[0.01034939,0.0007720867,0.0009885964,0.004051087,0.00323964,0.004609983,0.003082155,0.00408359,0.001163846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00187624,"about_ca_system_score_gemma":0.0008870068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001097859,"about_ca_topic_score_gemma":0.0005352977,"domain_scores_codex":[0.9968418,0.001484097,0.0001673294,0.0002768149,0.001118831,0.0001111981],"domain_scores_gemma":[0.9923542,0.006181336,0.0002977047,0.0003845199,0.0006932043,0.00008902176],"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":[0.0001997141,0.0001524733,0.001496962,0.001606551,0.0001633386,0.0001268165,0.00035977,0.03932635,0.002615245,0.372122,0.003994217,0.5778365],"study_design_scores_gemma":[0.0001469417,0.001156379,0.001638876,0.00179076,0.000203713,0.0005001431,0.0003626079,0.1218905,0.01750454,0.3478427,0.5066595,0.0003033529],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01483369,0.2834789,0.6611882,0.005909767,0.001304144,0.0003210259,0.0004031351,0.0007487618,0.03181215],"genre_scores_gemma":[0.2599815,0.3765112,0.343813,0.004078642,0.004388233,0.0007658945,0.0008662887,0.0006990748,0.008896062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008026902,"threshold_uncertainty_score":0.04245079,"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."}}