{"id":"W2047211642","doi":"10.1371/journal.pone.0088163","title":"Use of Sequenom Sample ID Plus® SNP Genotyping in Identification of FFPE Tumor Samples","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"Ontario Ministry of Research and Innovation; Prostate Cancer Canada; Ontario Institute for Cancer Research; Movember Foundation","keywords":"Genotyping; Molecular Inversion Probe; Microsatellite; SNP genotyping; Biology; Amplicon; Polymerase chain reaction; DNA profiling; STR analysis; STR multiplex system; Single-nucleotide polymorphism; DNA extraction; SNP array; Genetics; Genotype; Computational biology; DNA; Multiplex polymerase chain reaction; Gene; Allele","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":[0.003372986,0.0005965969,0.0005147478,0.001017544,0.0004668013,0.0006442748,0.0004169962,0.0008068809,0.001138222],"category_scores_gemma":[0.004059662,0.0003860288,0.0002787338,0.0005505966,0.000361026,0.0002666209,0.0003451547,0.0003712642,0.0007966396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001985235,"about_ca_system_score_gemma":0.0003714154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000557963,"about_ca_topic_score_gemma":0.001599341,"domain_scores_codex":[0.9961377,0.001231913,0.0003118794,0.001089734,0.001072889,0.0001558895],"domain_scores_gemma":[0.998293,0.0008519309,0.0002033654,0.0002283634,0.0003660477,0.00005733686],"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":[0.0006786865,0.0001031197,0.01625158,0.0002085417,0.00006322402,0.0003255075,0.0001943896,0.0006288574,0.950424,0.0001796453,0.0003017421,0.03064081],"study_design_scores_gemma":[0.00002712048,0.0007359224,0.04262437,0.00003879653,0.0001464004,0.001792503,0.0000556467,0.004614358,0.9434696,0.0002108634,0.0062511,0.00003328376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7909247,0.00349656,0.1979423,0.0001991208,0.0001134344,0.0009784285,0.001829724,0.0006818771,0.003833875],"genre_scores_gemma":[0.5636048,0.001764951,0.4264633,0.0004091388,0.00002787692,0.001252525,0.002946704,0.0001547889,0.003375902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003372986,"threshold_uncertainty_score":0.01783824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07264150466602563,"score_gpt":0.2693159023288592,"score_spread":0.1966743976628336,"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."}}