{"id":"W2969911993","doi":"10.1038/s42003-019-0596-y","title":"Quantitative comparative analysis of human erythrocyte surface proteins between individuals from two genetically distinct populations","year":2019,"lang":"en","type":"article","venue":"Communications Biology","topic":"Erythrocyte Function and Pathophysiology","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Cambridge Institute for Medical Research, University of Cambridge; Canadian Institutes of Health Research; National Institutes of Health; Evelyn Trust; NIHR Cambridge Biomedical Research Centre; Wellcome Trust; Wellcome; National Institute of Allergy and Infectious Diseases; Bill and Melinda Gates Foundation","keywords":"Proteome; Biology; Erythrocyte membrane; Membrane protein; Red blood cell; Malaria; Computational biology; Receptor; Proteomics; Cell biology; Immunology; Genetics; Gene; Membrane","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000202873,0.0001765308,0.0009492468,0.000287257,0.0001904357,0.000007181218,0.0004519742,0.0001592154,0.0005281351],"category_scores_gemma":[0.00008830787,0.0001575115,0.0002194617,0.0009078541,0.0006165633,0.00004340566,0.0003008158,0.000305536,0.0001327477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004803939,"about_ca_system_score_gemma":0.00008001333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008400564,"about_ca_topic_score_gemma":0.000789701,"domain_scores_codex":[0.9981051,0.0006500882,0.0006227622,0.0003300392,0.00009707548,0.0001949435],"domain_scores_gemma":[0.9966325,0.0008658875,0.0003634289,0.00173515,0.0003108912,0.0000921556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004936546,0.0001709186,0.9025973,0.000007816313,0.001567342,1.395176e-7,0.0007715906,0.0001224816,0.06729036,0.0272145,0.00004005191,0.0001680975],"study_design_scores_gemma":[0.0009738489,0.0008248197,0.9889392,0.00002699712,0.001514795,6.48535e-7,0.0003952111,0.002278196,0.001104224,0.002550286,0.001225749,0.0001660778],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910989,0.0005443752,0.002318036,0.0006489184,0.00005660392,0.000658915,0.0006717544,0.00005361524,0.003948846],"genre_scores_gemma":[0.9542786,0.00005076178,0.0376002,0.00009870675,0.00002867378,0.00002614775,0.007768387,0.00001031789,0.0001381445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08634181,"threshold_uncertainty_score":0.6423132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1754658694568861,"score_gpt":0.4298107543329329,"score_spread":0.2543448848760468,"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."}}