{"id":"W4321376551","doi":"10.1016/j.immuno.2023.100025","title":"AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets","year":2023,"lang":"en","type":"article","venue":"ImmunoInformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health; Vetenskapsrådet; National Institute of Allergy and Infectious Diseases; Canadian Institutes of Health Research; European Commission","keywords":"Germline; Interoperability; Computational biology; Biology; Data curation; Computer science; Genetics; Gene; Data science; World Wide Web","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":[0.04973801,0.002011008,0.002466211,0.02493676,0.005218962,0.007195011,0.006859024,0.002891201,0.01294268],"category_scores_gemma":[0.1336502,0.001370235,0.004129391,0.01696455,0.002766884,0.005888461,0.0157348,0.005186892,0.01229339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003522734,"about_ca_system_score_gemma":0.01768015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293899,"about_ca_topic_score_gemma":0.02166276,"domain_scores_codex":[0.9561936,0.01328535,0.008424105,0.008109171,0.0123185,0.001669252],"domain_scores_gemma":[0.8911256,0.02395208,0.006700385,0.04462346,0.03065811,0.002940352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001079368,0.0003486165,0.01365068,0.01179266,0.001270539,0.002915823,0.01209513,0.01128178,0.061837,0.1486941,0.2954742,0.43956],"study_design_scores_gemma":[0.0001512511,0.00009828449,0.005534652,0.002131684,0.0003033153,0.0009470826,0.001092077,0.0109207,0.02153139,0.06443889,0.8925647,0.0002859676],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01099354,0.001702204,0.8161138,0.002783336,0.001269198,0.002711941,0.1008557,0.03593641,0.02763391],"genre_scores_gemma":[0.02900068,0.0007370576,0.786054,0.0009467633,0.0002708039,0.004063337,0.1614274,0.009682126,0.007817888],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04973801,"threshold_uncertainty_score":0.2630429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02295008972932137,"score_gpt":0.2801263588768214,"score_spread":0.2571762691475,"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."}}