{"id":"W1986245245","doi":"10.1021/ja0039942","title":"Generation of Highly Enantioselective Catalysts from the Pseudoenatiomeric Assembly of BINOL, F<sub>8</sub>BINOL, and Ti(O<i>i</i>Pr)<sub>4</sub>","year":2001,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Traditional and Medicinal Uses of Annonaceae","field":"Biochemistry, Genetics and Molecular Biology","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Citation; Enantioselective synthesis; Library science; George (robot); Social media; Computer science; World Wide Web; Chemistry; Nanotechnology; Information retrieval; Catalysis; Artificial intelligence; Materials science; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002260676,0.0004681928,0.0001961307,0.0005000422,0.000203937,0.0004033627,0.0004238565,0.0002722795,0.004336156],"category_scores_gemma":[0.0003214923,0.0002662813,0.0002319917,0.0002920024,0.0001371533,0.0005334622,0.0003537926,0.0007431481,0.001777861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003980182,"about_ca_system_score_gemma":0.0002138109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006440035,"about_ca_topic_score_gemma":0.002223832,"domain_scores_codex":[0.9998029,0.00001899663,0.00001213229,0.00003816323,0.00005880037,0.00006900985],"domain_scores_gemma":[0.9999315,0.00001196861,0.00001420838,0.000009736833,0.00001668842,0.00001601615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001507917,0.00008848075,0.0002832203,0.0001694194,0.00002648445,0.0001671487,0.0001173873,0.0004628252,0.9667086,0.002236757,0.002511518,0.02707736],"study_design_scores_gemma":[0.00001586192,0.0001069875,0.0003112497,0.000008171803,0.00001166381,0.00007516355,0.00003946596,0.001739456,0.9900816,0.0001253703,0.007476328,0.000008640071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914983,0.00326531,0.03505599,0.0006269731,0.0004669352,0.0002411293,0.001191802,0.0008176303,0.0668359],"genre_scores_gemma":[0.9772915,0.001254077,0.007440735,0.00009932838,0.00002090326,0.00004266791,0.00104209,0.0001511956,0.01265745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004336156,"threshold_uncertainty_score":0.01450586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270619282703393,"score_gpt":0.2329306963403028,"score_spread":0.2202245035132688,"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."}}