{"id":"W2994889061","doi":"10.1073/pnas.1909798116","title":"A bacterial surface layer protein exploits multistep crystallization for rapid self-assembly","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Enzyme Structure and Function","field":"Materials Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Government of Canada; U.S. Department of Energy","keywords":"Nucleation; Crystallization; Caulobacter crescentus; Protein crystallization; Self-assembly; Crystallography; Materials science; Biophysics; S-layer; Macromolecule; Chemical physics; Nanotechnology; Chemistry; Biochemistry; Biology; Bacterial protein","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000186628,0.0003507122,0.0001946407,0.0001438541,0.0001901938,0.0002731796,0.0002992875,0.0003036637,0.0003254141],"category_scores_gemma":[0.000155918,0.0001629164,0.000256161,0.0001347759,0.0002650404,0.0002056094,0.0003298692,0.0003990107,0.0002499683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004749704,"about_ca_system_score_gemma":0.0002858895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001197079,"about_ca_topic_score_gemma":0.001414021,"domain_scores_codex":[0.9998715,0.00001740073,0.000007141919,0.00003020846,0.00004777009,0.0000259042],"domain_scores_gemma":[0.9999216,0.00001389132,0.00002231824,0.00001564719,0.000009617145,0.00001693141],"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":[0.00002196348,0.00001498228,0.0001287633,0.00001446114,0.00000203992,0.00002154763,0.000008800147,0.0001635078,0.9980643,0.0001455988,0.00002800604,0.001385933],"study_design_scores_gemma":[0.000004025521,0.00005299142,0.0004549768,0.000001302584,0.000002157783,0.000093308,0.00000377296,0.002246078,0.9961653,0.00002509959,0.0009479059,0.000003176048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97689,0.001060162,0.02033554,0.0001423309,0.00003321314,0.00005488443,0.0001287625,0.0002979244,0.001057236],"genre_scores_gemma":[0.9733228,0.0005385499,0.02388219,0.00003326161,0.000005535519,0.00003206125,0.0002108165,0.00004957067,0.001925211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001197079,"threshold_uncertainty_score":0.003446221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042483032529826,"score_gpt":0.2752256289712722,"score_spread":0.2448007986459739,"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."}}