{"id":"W193258566","doi":"10.1007/978-1-4614-1587-9_18","title":"Bead-based arrays: multiplex analyses","year":2011,"lang":"en","type":"book-chapter","venue":"Food engineering series","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Multiplex; Analyte; Biomolecule; Multiplexing; Computational biology; Nanotechnology; Computer science; Biochemical engineering; Chemistry; Materials science; Biology; Chromatography; Bioinformatics; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004190608,0.0005455887,0.0004861623,0.0002860106,0.00005350033,0.00004725119,0.0001572913,0.0004523472,0.0002954051],"category_scores_gemma":[0.0000171548,0.0005644199,0.000280972,0.00006543237,0.00006225619,0.0001031076,0.00002148921,0.0004580295,0.0001321397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006723653,"about_ca_system_score_gemma":0.00001327291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004856493,"about_ca_topic_score_gemma":0.00001421357,"domain_scores_codex":[0.9988744,0.000002905116,0.0003293152,0.0002863749,0.0001758834,0.0003311419],"domain_scores_gemma":[0.9994614,0.00003507033,0.00004148918,0.0003108435,0.00003828654,0.0001129216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005123537,0.00003051338,0.000005268485,0.002207388,0.002168257,0.00006885934,0.0001554148,0.8937154,0.01858902,0.07679461,0.002454961,0.003759072],"study_design_scores_gemma":[0.0007924922,0.001538493,0.0001111672,0.001499129,0.0008645577,0.00005205418,0.00002046231,0.1756895,0.1403472,0.004818015,0.6699193,0.00434758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003093967,0.01274111,0.1271677,0.0001312503,0.005405406,0.001226712,0.0009560939,0.01411774,0.83516],"genre_scores_gemma":[0.912597,0.0007006902,0.01180406,0.00006931284,0.001563565,0.0000595205,0.000213326,0.0009944963,0.071998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.909503,"threshold_uncertainty_score":0.9996807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04147954273832574,"score_gpt":0.2078397901988531,"score_spread":0.1663602474605274,"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."}}