{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001576233,0.0002852315,0.0001617385,0.00008782066,0.0001243085,0.0001771161,0.0002211889,0.0003111309,0.002967467],"category_scores_gemma":[0.000330092,0.00008081183,0.0001939093,0.00009171553,0.0001583314,0.0001857528,0.0001148047,0.0002828764,0.0005636028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003246741,"about_ca_system_score_gemma":0.0001684067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054099,"about_ca_topic_score_gemma":0.00109879,"domain_scores_codex":[0.9999086,0.00001828957,0.000005864526,0.00002541067,0.00001918658,0.00002264553],"domain_scores_gemma":[0.9998677,0.0000389248,0.00002696108,0.000009317687,0.00001956333,0.0000375331],"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":[0.0002200586,0.00002362234,0.000345142,0.00003768095,0.000005855169,0.0000754004,0.00001339339,0.00008715733,0.997923,0.00005157886,0.0001235618,0.001093542],"study_design_scores_gemma":[0.00003477676,0.0005255691,0.005638563,0.000008268574,0.0000115662,0.0006359831,0.00002805149,0.001696099,0.9887827,0.00004354215,0.002584897,0.00001001803],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947936,0.0006010038,0.002222136,0.00017955,0.00003438265,0.00002760445,0.0003467769,0.00004887771,0.001746058],"genre_scores_gemma":[0.9932095,0.0002204034,0.002785235,0.0001002594,0.00000982773,0.00001760595,0.000875979,0.00001563673,0.002765545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002967467,"threshold_uncertainty_score":0.009927213,"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."}}