{"id":"W4235401656","doi":"10.1515/iupac.86.0011","title":"Immunodiagnostics and Immunosensor Design","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Computer science; Data science; Nanotechnology; Biochemical engineering; Computational biology; Risk analysis (engineering); Medicine; Biology; Engineering; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002582775,0.001272087,0.001386311,0.005319229,0.0004484103,0.002457842,0.001330615,0.001003006,0.02429262],"category_scores_gemma":[0.01244954,0.0004531421,0.001153096,0.00980777,0.0003657711,0.001199126,0.001150645,0.001466026,0.01903001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001705464,"about_ca_system_score_gemma":0.002814781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006185898,"about_ca_topic_score_gemma":0.00700352,"domain_scores_codex":[0.9963223,0.0007044902,0.0008191736,0.0008742932,0.001021396,0.0002583314],"domain_scores_gemma":[0.9961839,0.00193727,0.0004645636,0.0004471757,0.0008586678,0.0001082903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005148354,0.00008791532,0.01523915,0.01972137,0.000489671,0.000185016,0.0000876578,0.005824724,0.002182098,0.01005781,0.5541812,0.3914286],"study_design_scores_gemma":[0.00005355127,0.00004737201,0.004868314,0.0008128746,0.0001120406,0.0002826809,0.0000449581,0.001193782,0.001981708,0.006617671,0.9839609,0.00002422649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003593094,0.03557788,0.02011954,0.001714925,0.0005053362,0.0006043943,0.9118336,0.002487576,0.02356376],"genre_scores_gemma":[0.01872961,0.03256913,0.03420852,0.001526512,0.0002085107,0.001631832,0.9024094,0.0004705075,0.008246025],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02429262,"threshold_uncertainty_score":0.08126688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275986365168881,"score_gpt":0.3873172781935199,"score_spread":0.3745574145418311,"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."}}