{"id":"W2069192750","doi":"10.1016/j.jmoldx.2014.04.004","title":"Genotyping Single Nucleotide Polymorphisms in Human Genomic DNA with an Automated and Self-Contained PCR Cassette","year":2014,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Genotyping; Single-nucleotide polymorphism; Molecular Inversion Probe; SNP genotyping; Melting curve analysis; Buccal swab; Genotype; Biology; genomic DNA; SNP array; Genetics; Point mutation; Allele; Polymerase chain reaction; Computational biology; DNA; Gene; Mutation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003617285,0.0002412715,0.000329312,0.0001559093,0.00007977332,0.00008780594,0.0002364453,0.0001501093,0.000003134377],"category_scores_gemma":[0.0002783539,0.0002323497,0.00007267265,0.0001049719,0.00007709456,0.00001268783,0.00009689248,0.0001805221,0.000001129695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007803568,"about_ca_system_score_gemma":0.0001350148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004949049,"about_ca_topic_score_gemma":0.0002163235,"domain_scores_codex":[0.9986069,0.0001146565,0.0004851594,0.0002817656,0.0001844133,0.0003270749],"domain_scores_gemma":[0.9988287,0.00008627083,0.0003603302,0.0003184749,0.0001782732,0.0002279482],"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":[0.0001284944,0.0003681301,0.01434609,0.00002093645,0.0001172763,0.0003035995,0.000130027,0.001701181,0.9813684,0.0002552866,0.0002979339,0.0009626813],"study_design_scores_gemma":[0.01137024,0.01548274,0.1630358,0.0004429201,0.0006896507,0.001608378,0.0002330934,0.005118919,0.7776605,0.001348295,0.02106884,0.001940652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949242,0.001611631,0.002849652,0.0001747182,0.0001348487,0.0001574899,0.00001131903,0.00002004852,0.0001160862],"genre_scores_gemma":[0.9928262,0.0005556354,0.005408486,0.0007933562,0.0003135719,0.0000039013,0.00003074936,0.00006368482,0.000004402462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2037078,"threshold_uncertainty_score":0.9474947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005655448701091868,"score_gpt":0.2269196315513112,"score_spread":0.2212641828502193,"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."}}