{"id":"W2902579141","doi":"10.1172/jci.insight.121867","title":"A standardized immune phenotyping and automated data analysis platform for multicenter biomarker studies","year":2018,"lang":"en","type":"article","venue":"JCI Insight","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Terry Fox Research Institute; University of Manitoba; Shared Health; CancerCare Manitoba; Hôpital Maisonneuve-Rosemont; Université de Montréal; University of Alberta; BC Children's Hospital; Manitoba Health; Toronto General Hospital; University of Toronto; University of British Columbia","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institute of Allergy and Infectious Diseases; Canadian Institutes of Health Research","keywords":"Biomarker; Immune system; Medicine; Computer science; Computational biology; Data science; Internal medicine; Medical physics; Immunology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002107263,0.0001515166,0.0002673866,0.00007528927,0.0001718332,0.00004297068,0.0001936083,0.0001015423,0.000009850535],"category_scores_gemma":[0.0001192651,0.0001225411,0.00008557251,0.0001532513,0.0001607423,0.00001185121,0.0001828052,0.00003441961,0.000001856574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001249348,"about_ca_system_score_gemma":0.00002695623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002628046,"about_ca_topic_score_gemma":0.0002115729,"domain_scores_codex":[0.9990469,0.00002114803,0.0002424447,0.0004075678,0.00007971811,0.0002022417],"domain_scores_gemma":[0.9991592,0.00002777395,0.00007429146,0.0005129945,0.000178015,0.0000477782],"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":[0.001524344,0.0001251445,0.002491678,0.00008431464,0.004647035,0.000002172799,0.0007977103,0.000004742224,0.9788591,0.00003958102,0.00297653,0.008447646],"study_design_scores_gemma":[0.01067797,0.0008402319,0.01062241,0.0001012284,0.002702208,0.000006794034,0.0006906218,0.1575031,0.5320056,0.0001334088,0.2836247,0.001091695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.972136,0.004675636,0.02167138,0.0001074942,0.000364099,0.0003477751,0.0002782483,0.0000728279,0.0003464918],"genre_scores_gemma":[0.9927396,0.0003687387,0.005771666,0.0001719948,0.0001703933,0.00001404958,0.000615467,0.00002030983,0.0001277397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4468535,"threshold_uncertainty_score":0.4997079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08095879672373672,"score_gpt":0.3450819695409605,"score_spread":0.2641231728172238,"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."}}