{"id":"W2256283611","doi":"10.1038/ncomms8996","title":"The molecular mechanism of Zinc acquisition by the neisserial outer-membrane transporter ZnuD","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Trace Elements in Health","field":"Nursing","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; Hospital for Sick Children; Canada Research Chairs; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canadian Light Source; Ministère de l’Éducation, Gouvernement de l’Ontario; Compute Canada; McGill University","keywords":"Mechanism (biology); Transporter; Bacterial outer membrane; Zinc; Chemistry; ATP-binding cassette transporter; Cell biology; Computational biology; Biochemistry; Biophysics; Biology; Gene; Physics; Escherichia coli","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":[0.00009160418,0.0002547551,0.0002138011,0.0001223071,0.0003024519,0.0004536834,0.0004686606,0.000535815,0.000437289],"category_scores_gemma":[0.0001274829,0.000159301,0.000277704,0.00006681215,0.000462128,0.0004533089,0.0002030531,0.0003193963,0.0001295582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005984283,"about_ca_system_score_gemma":0.0003116356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002463337,"about_ca_topic_score_gemma":0.001485889,"domain_scores_codex":[0.999967,0.000004719476,0.000002117335,0.000008718784,0.000007483661,0.000009893687],"domain_scores_gemma":[0.9999759,0.000005616225,0.000006436787,0.000003138254,0.000002762807,0.000006193245],"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":[0.0003270378,0.00007666429,0.00295521,0.0001527278,0.00002765727,0.000556929,0.00008799905,0.006107686,0.9737098,0.01053366,0.0001894689,0.005275227],"study_design_scores_gemma":[0.0001614918,0.0003467812,0.005807315,0.00002598071,0.00004195388,0.0005319297,0.0002219889,0.1064349,0.879229,0.003566328,0.00359109,0.00004123347],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841643,0.001247016,0.01237995,0.0004450259,0.00002971622,0.00002925063,0.00005587761,0.0001111064,0.001537767],"genre_scores_gemma":[0.9950446,0.0007497113,0.003579629,0.0000247878,0.000004601525,0.00001042023,0.00003417994,0.000004273961,0.0005477653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002463337,"threshold_uncertainty_score":0.004898012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02287102772014317,"score_gpt":0.3261450914869974,"score_spread":0.3032740637668543,"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."}}