{"id":"W2811364409","doi":"10.1111/imr.12666","title":"iReceptor: A platform for querying and analyzing antibody/B‐cell and T‐cell receptor repertoire data across federated repositories","year":2018,"lang":"en","type":"review","venue":"Immunological Reviews","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":186,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canada Foundation for Innovation; Canarie; National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Burroughs Wellcome Fund","keywords":"Metadata; Computer science; Workflow; Data sharing; Medicine; Computational biology; Data mining; Data science; World Wide Web; Database; Biology","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":[0.01461618,0.002768829,0.002828968,0.006281187,0.001299321,0.007441069,0.009016623,0.00305957,0.006992516],"category_scores_gemma":[0.01275533,0.002694342,0.002639499,0.005277946,0.00159913,0.008971376,0.008703173,0.005082168,0.01131217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001913791,"about_ca_system_score_gemma":0.003398065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005167795,"about_ca_topic_score_gemma":0.004515911,"domain_scores_codex":[0.9936418,0.001279104,0.0007469054,0.001378519,0.002566436,0.0003871764],"domain_scores_gemma":[0.9917699,0.002665471,0.000866731,0.002607876,0.001304794,0.0007852787],"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":[0.002400926,0.0003496663,0.007962518,0.006034713,0.00178926,0.001155297,0.001805262,0.016012,0.1146359,0.06010323,0.451056,0.3366952],"study_design_scores_gemma":[0.0006314907,0.0003976038,0.006715921,0.001300554,0.0004651106,0.001606136,0.0005215593,0.07924349,0.07811249,0.07783919,0.7523642,0.0008022676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.007182483,0.006798315,0.5852031,0.002524405,0.0006070742,0.0007051579,0.04575209,0.3430203,0.008207125],"genre_scores_gemma":[0.03853209,0.007649084,0.7026451,0.002781197,0.0003580053,0.001572113,0.2192906,0.0205162,0.006655644],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01461618,"threshold_uncertainty_score":0.07729876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1178170063987545,"score_gpt":0.3795835212828724,"score_spread":0.2617665148841179,"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."}}