{"id":"W2095885244","doi":"10.1093/bioinformatics/bth439","title":"Primer Design and Marker Clustering for Multiplex SNP-IT Primer Extension Genotyping Assay using Statistical Modeling","year":2004,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"","keywords":"Primer (cosmetics); Genotyping; Cluster analysis; Primer extension; Multiplex; SNP genotyping; SNP; Computer science; Statistical model; Computational biology; Biology; Genetics; Single-nucleotide polymorphism; Genotype; Artificial intelligence; Chemistry; Gene","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":[0.00722188,0.001875657,0.001703452,0.001897117,0.0008687104,0.00116059,0.002178478,0.001812604,0.006101337],"category_scores_gemma":[0.01738625,0.001801382,0.001739084,0.002277375,0.0008345088,0.001063589,0.001068113,0.002572933,0.006261862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009506553,"about_ca_system_score_gemma":0.002155763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006003836,"about_ca_topic_score_gemma":0.001017593,"domain_scores_codex":[0.9927987,0.003249382,0.000765529,0.001715063,0.001207995,0.0002633165],"domain_scores_gemma":[0.9919122,0.004513641,0.0008686297,0.001306479,0.001243829,0.0001551404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001607331,0.0005183308,0.006458262,0.002497273,0.0004185123,0.0005853093,0.0005326853,0.1138462,0.5259467,0.03768683,0.01591011,0.2939925],"study_design_scores_gemma":[0.0001806381,0.0006530614,0.002336888,0.0001351035,0.0002641213,0.001063419,0.00005888606,0.4916334,0.4318352,0.02470908,0.04688691,0.0002432306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003037218,0.0001057143,0.99421,0.00005132818,0.00003395602,0.0002683502,0.0002944733,0.001780575,0.000218337],"genre_scores_gemma":[0.01054827,0.00008347796,0.9868985,0.00007081,0.00001386914,0.0009738721,0.0006623861,0.0003146678,0.0004341607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00722188,"threshold_uncertainty_score":0.0381934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06619816459178136,"score_gpt":0.3131831912085179,"score_spread":0.2469850266167365,"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."}}