{"id":"W1964727438","doi":"10.1016/j.jim.2005.09.020","title":"Multiple cellular antigen detection by ICP-MS","year":2005,"lang":"en","type":"article","venue":"Journal of Immunological Methods","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":149,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; University of Toronto","funders":"National Cancer Institute; Ontario Genomics Institute; Genome Canada","keywords":"Multiplex; Antigen; Flow cytometry; Immunophenotyping; Molecular biology; Mass cytometry; Immunoassay; Antibody; Biology; Chemistry; Cell biology; Immunology; Biochemistry; Bioinformatics","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":[0.0006529646,0.001089896,0.0006028449,0.001094825,0.0006917907,0.0009909231,0.0009934726,0.000904489,0.00388192],"category_scores_gemma":[0.0006822971,0.0004286089,0.0003760388,0.0008115898,0.0005606683,0.001105178,0.000656098,0.00177919,0.002334439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007041093,"about_ca_system_score_gemma":0.0005682685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004973118,"about_ca_topic_score_gemma":0.0006568368,"domain_scores_codex":[0.9992927,0.00008242753,0.00004276023,0.0002383039,0.0002618899,0.0000819219],"domain_scores_gemma":[0.9995694,0.0001344016,0.00003544286,0.00007939463,0.000136603,0.00004485737],"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":[0.00004775142,0.00003249021,0.0001124395,0.00007096955,0.000009560973,0.000050932,0.00003828195,0.00005828267,0.9901121,0.0008093155,0.0006214636,0.008036399],"study_design_scores_gemma":[0.000007416975,0.00004518128,0.0004581702,0.000003820823,0.000008712154,0.0002738179,0.00002006219,0.00146593,0.9913967,0.000501812,0.005811325,0.000007088107],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3431751,0.003345776,0.6162453,0.00115196,0.001021693,0.0002653539,0.001263922,0.006290105,0.02724085],"genre_scores_gemma":[0.5643969,0.002555036,0.4075527,0.0006475227,0.0002598893,0.0005686544,0.001756058,0.0009154741,0.02134773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00388192,"threshold_uncertainty_score":0.01298636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02484503822957469,"score_gpt":0.3484409744407223,"score_spread":0.3235959362111476,"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."}}