{"id":"W40733668","doi":"10.1096/fasebj.20.4.a100-a","title":"Multiplex Biomarker Detection by ICP‐MS","year":2006,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"Ontario Genomics Institute","keywords":"Multiplex; Biomarker; Computational biology; Biology; Bioinformatics; Genetics","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":[0.001269241,0.001094592,0.0008430475,0.001358667,0.0004337473,0.001167703,0.001494139,0.001183429,0.001795296],"category_scores_gemma":[0.001011958,0.0006708583,0.000435702,0.0007662968,0.0005786287,0.001159205,0.001175781,0.001331903,0.001092055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000688973,"about_ca_system_score_gemma":0.0004042091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002954158,"about_ca_topic_score_gemma":0.000299606,"domain_scores_codex":[0.9981937,0.00026995,0.00009573897,0.0005236461,0.0008008301,0.0001161304],"domain_scores_gemma":[0.9995472,0.0001655359,0.00006464907,0.00005952083,0.0001259616,0.00003706554],"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":[0.0001007283,0.00006360409,0.0003146384,0.0001468147,0.00002844361,0.0001228658,0.00007780831,0.0004739861,0.9704741,0.001099972,0.0006570244,0.02644003],"study_design_scores_gemma":[0.00001460724,0.0001321028,0.0003137233,0.00001105006,0.00002646362,0.0004335757,0.00002578955,0.007646922,0.9820249,0.0009423756,0.008399267,0.000029203],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1479971,0.006122638,0.8350701,0.0005360274,0.0006446062,0.0003432709,0.0006697007,0.003541663,0.005074928],"genre_scores_gemma":[0.3508633,0.004956788,0.633237,0.0003721367,0.0002742934,0.000947555,0.0006124107,0.0001644928,0.008571968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001795296,"threshold_uncertainty_score":0.006712437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008140801214737365,"score_gpt":0.192939639816496,"score_spread":0.1847988386017586,"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."}}