{"id":"W2901659109","doi":"10.1039/c8mt00274f","title":"The N-terminal 14-mer model peptide of human Ctr1 can collect Cu(<scp>ii</scp>) from albumin. Implications for copper uptake by Ctr1","year":2018,"lang":"en","type":"article","venue":"Metallomics","topic":"Trace Elements in Health","field":"Nursing","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatoon Medical Imaging; University of Saskatchewan","funders":"National Center for Research Resources; National Institutes of Health; Fondation Pour la Recherche en Chimie; Zhejiang Academy of Agricultural Sciences; Ministerstwo Edukacji i Nauki; Narodowe Centrum Nauki; Fundacja na rzecz Nauki Polskiej; Research Corporation for Science Advancement; U.S. Department of Energy","keywords":"Copper; Human serum albumin; Peptide; Transporter; Chemistry; Albumin; Human albumin; Terminal (telecommunication); Biochemistry; Gene; Computer science; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005902287,0.000312109,0.0004423039,0.00008749717,0.001598831,0.00007917506,0.0007000084,0.0001724144,0.00001119476],"category_scores_gemma":[0.0002978139,0.000271869,0.0002026196,0.0002256027,0.0004150358,0.0001244712,0.0001192353,0.0002600326,0.00001291479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002889552,"about_ca_system_score_gemma":0.0001797154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004972694,"about_ca_topic_score_gemma":0.003078164,"domain_scores_codex":[0.9975352,0.00009776486,0.0008114297,0.0005288224,0.0002890436,0.0007377248],"domain_scores_gemma":[0.99749,0.0006260226,0.0004497431,0.000956477,0.000304599,0.0001730857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002318259,0.0007040519,0.002768172,0.00009036499,0.0005048083,8.621857e-7,0.007245749,0.0001655412,0.3515888,0.005742996,0.6227344,0.008222324],"study_design_scores_gemma":[0.007839912,0.004298158,0.01738688,0.0001873484,0.001961584,0.00003937769,0.003257353,0.04295325,0.3608938,0.05841883,0.5016236,0.001139939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907166,0.0003369062,0.001368957,0.002520476,0.0007033895,0.001278245,0.001497788,0.00007900861,0.001498581],"genre_scores_gemma":[0.981774,0.00004067102,0.01050495,0.0008391137,0.0003798783,0.000270968,0.0002508398,0.0001137895,0.005825784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1211109,"threshold_uncertainty_score":0.9999734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04070502169843423,"score_gpt":0.3341263986793618,"score_spread":0.2934213769809276,"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."}}