{"id":"W4322582014","doi":"10.1039/d2sc07023e","title":"A convergent fragment coupling strategy to access quaternary stereogenic centers","year":2023,"lang":"en","type":"article","venue":"Chemical Science","topic":"Asymmetric Hydrogenation and Catalysis","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemistry; Division of Graduate Education; Beckman Institute, California Institute of Technology; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; California Institute of Technology","keywords":"Stereocenter; Fragment (logic); Quaternary; Coupling (piping); Computer science; Stereochemistry; Computational biology; Chemistry; Biology; Paleontology; Engineering; Algorithm; Enantioselective synthesis; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002276676,0.0001168599,0.0001219389,0.0001503056,0.0001241825,0.000134679,0.0009678843,0.00004536477,0.001008179],"category_scores_gemma":[0.00009654916,0.0001065413,0.00006952721,0.001945049,0.0001339987,0.0001767892,0.0004727169,0.0000943167,0.0005330481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002353135,"about_ca_system_score_gemma":0.00009279389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004211627,"about_ca_topic_score_gemma":9.013415e-7,"domain_scores_codex":[0.9982101,0.00000193385,0.0002189197,0.000470128,0.0006601629,0.0004387468],"domain_scores_gemma":[0.999172,0.00003421676,0.00005278904,0.0002918052,0.0000606739,0.0003884663],"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":[0.000008036923,0.00003672754,0.003101907,0.00002065999,0.00001246842,0.00001173652,0.00009527279,0.000576709,0.9911308,0.00004092733,0.0007954143,0.004169337],"study_design_scores_gemma":[0.0001597928,0.000006217725,0.0002190678,0.00001591867,0.000007978736,0.000002240118,0.0001706434,0.02449301,0.9735506,0.00003385679,0.001184777,0.0001558944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949256,0.00001895394,0.0001886893,0.000292468,0.0000963299,0.00005206034,0.00001001544,0.0001500045,0.004265863],"genre_scores_gemma":[0.9988525,0.00001489004,0.00002808744,0.0002031739,0.00005339111,0.00002483205,0.00002392138,0.000009121813,0.0007901074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0239163,"threshold_uncertainty_score":0.999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03456327842337851,"score_gpt":0.3147572844539283,"score_spread":0.2801940060305498,"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."}}