{"id":"W2884939853","doi":"10.1002/cyto.a.23495","title":"Tellurium‐based mass cytometry barcode for live and fixed cells","year":2018,"lang":"en","type":"article","venue":"Cytometry Part A","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fluidigm (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Mass cytometry; Barcode; Microscale chemistry; Flow cytometry; Cytometry; Biology; Sample preparation; Chemistry; Computational biology; Molecular biology; Chromatography; Computer science; Biochemistry; Phenotype; Mathematics","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":[0.0008616142,0.0005509873,0.0004080939,0.001015525,0.0007418544,0.000802184,0.001165623,0.001228087,0.002928997],"category_scores_gemma":[0.001871648,0.0003291373,0.0003783406,0.000618319,0.0009014368,0.0008686115,0.000852732,0.001627033,0.001822953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008516033,"about_ca_system_score_gemma":0.0006345622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007733511,"about_ca_topic_score_gemma":0.001621228,"domain_scores_codex":[0.9990587,0.0001526619,0.0000557704,0.0002222971,0.0004302517,0.00008029713],"domain_scores_gemma":[0.9986829,0.0004509205,0.0002659785,0.0001675573,0.0003563857,0.00007615436],"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":[0.00004833388,0.00001038007,0.0001499158,0.0001008887,0.000007596163,0.00004422994,0.0000578048,0.0002954981,0.9864676,0.002363885,0.0005666083,0.009887128],"study_design_scores_gemma":[0.000003718233,0.00003569995,0.0002576989,0.0000107229,0.000006290356,0.0001189581,0.00001461457,0.003304688,0.9868898,0.0002484985,0.009095825,0.00001345947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1061625,0.002618971,0.8789114,0.0009874512,0.0005909102,0.0002913924,0.0009918256,0.002889466,0.006556192],"genre_scores_gemma":[0.321422,0.00336747,0.6565874,0.0007857537,0.0001724925,0.0006977423,0.001675291,0.0004582441,0.0148337],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002928997,"threshold_uncertainty_score":0.009798467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443999623773564,"score_gpt":0.2870282726106211,"score_spread":0.2725882763728855,"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."}}