{"id":"W2077887814","doi":"10.1021/jacs.5b02034","title":"Cellulose Nanocrystals as Chiral Inducers: Enantioselective Catalysis and Transmission Electron Microscopy 3D Characterization","year":2015,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; McGill University; Centre in Green Chemistry and Catalysis","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Enantioselective synthesis; Chemistry; Cellulose; Transmission electron microscopy; Catalysis; Enantiomer; High-resolution transmission electron microscopy; Chemical engineering; Nanotechnology; Kinetic resolution; Molecule; Combinatorial chemistry; Organic chemistry; Materials science","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":[0.0005273807,0.0001671034,0.0004062024,0.00002559477,0.0001493093,0.00005742659,0.0003186485,0.00004921945,0.00001170327],"category_scores_gemma":[0.0002060827,0.0001029732,0.0002133755,0.0004271502,0.0006336046,0.000286718,0.000139487,0.0003497788,0.000004125844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003347104,"about_ca_system_score_gemma":0.0002351259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003450076,"about_ca_topic_score_gemma":2.14393e-7,"domain_scores_codex":[0.9983805,0.000136112,0.0003479911,0.0002117953,0.0005606972,0.000362949],"domain_scores_gemma":[0.9986334,0.00008749683,0.0006600173,0.0001447248,0.0002655112,0.0002088234],"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":[0.0001509425,0.00007092003,0.0001807416,0.00001275463,0.0000529219,0.000001803782,0.001681499,0.000003726286,0.9955679,0.000003248257,0.0003510593,0.001922524],"study_design_scores_gemma":[0.0004005145,0.0002299542,0.0002531892,0.00003828811,0.00005482259,0.00004077685,0.0005195278,0.00005010041,0.9967378,0.0002981044,0.001251854,0.0001250257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969729,0.0003537603,0.001491742,0.0009347667,0.00006593741,0.0001147538,0.000005629469,0.00001319698,0.0000472747],"genre_scores_gemma":[0.9941247,0.0005095986,0.004735168,0.0002304898,0.0001997934,0.000003766075,0.000003326377,0.00001815473,0.0001750321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003243426,"threshold_uncertainty_score":0.4199124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268769847869961,"score_gpt":0.29735371823953,"score_spread":0.2846660197608304,"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."}}