{"id":"W2034967713","doi":"10.1023/b:jcam.0000047813.47656.36","title":"Reverse-docking as a computational tool for the study of asymmetric organocatalysis","year":2004,"lang":"en","type":"article","venue":"Journal of Computer-Aided Molecular Design","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"New Brunswick Innovation Foundation","keywords":"Docking (animal); Enantioselective synthesis; Chemistry; Organocatalysis; Enantiomer; Cationic polymerization; Stereochemistry; Catalysis; Combinatorial chemistry; Computational chemistry; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.002790244,0.0002659321,0.0005632898,0.0007359633,0.0001963405,0.0002475615,0.001791028,0.00006080839,0.000002561656],"category_scores_gemma":[0.0005396131,0.0002084002,0.0004186222,0.001870991,0.00005637891,0.0005835785,0.0003092347,0.0002691499,0.000004592147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001726352,"about_ca_system_score_gemma":0.0007979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001865749,"about_ca_topic_score_gemma":5.682986e-7,"domain_scores_codex":[0.9962792,0.000624725,0.001162595,0.0003663986,0.001279407,0.0002877221],"domain_scores_gemma":[0.9939753,0.003023609,0.001139536,0.0005463171,0.001207548,0.0001076229],"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":[0.00007290295,0.0005713575,0.00002230184,0.00001673564,0.0004862335,0.0001174261,0.0008242651,0.9543898,0.0005142629,0.01042762,0.0001674348,0.03238965],"study_design_scores_gemma":[0.006558983,0.004160286,0.002412005,0.0001532743,0.0004089968,0.0008950041,0.0001972411,0.8562938,0.01035329,0.1178507,0.0002201409,0.0004963044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08158664,0.0002893191,0.9160697,0.0007324136,0.0005124438,0.0007695092,0.000001463844,0.00002595376,0.00001255516],"genre_scores_gemma":[0.5349154,0.000004154156,0.4646669,0.0002976589,0.00008831116,0.000008543983,8.206103e-7,0.00001595775,0.000002232336],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4533288,"threshold_uncertainty_score":0.8498313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799403336623817,"score_gpt":0.3050360797353006,"score_spread":0.2770420463690624,"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."}}