{"id":"W2013727620","doi":"10.2144/000113369","title":"Improving Sequencing Quality from PCR Products Containing Long Mononucleotide Repeats","year":2010,"lang":"en","type":"article","venue":"BioTechniques","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"University of Guelph; Ontario Genomics Institute; Genome Canada","keywords":"Proofreading; Biology; Genetics; Polymerase; DNA polymerase; DNA; Polymerase chain reaction; Sequence (biology); Nucleotide; Microsatellite; Computational biology; Molecular biology; Allele; Gene","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":[0.00375001,0.0007708839,0.001069873,0.0007017212,0.0002908358,0.0009124229,0.0006700426,0.0008249852,0.00105035],"category_scores_gemma":[0.01183187,0.0005974729,0.0006557679,0.0006979064,0.000544994,0.0007862587,0.0005230602,0.001248116,0.001123909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002053066,"about_ca_system_score_gemma":0.0003755846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000207387,"about_ca_topic_score_gemma":0.0008278263,"domain_scores_codex":[0.9967306,0.00137864,0.0004217535,0.0005078886,0.0008006025,0.0001605134],"domain_scores_gemma":[0.9845375,0.007889142,0.002937041,0.001225712,0.0029933,0.0004173171],"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":[0.00008393754,0.00002342625,0.0008797019,0.0001938286,0.00002255637,0.00004966887,0.00008980389,0.000169843,0.9918739,0.00006229457,0.00004028039,0.006510664],"study_design_scores_gemma":[0.000004963589,0.0001376073,0.002751567,0.00002510204,0.00004206174,0.0002597024,0.00003106044,0.001071944,0.9945194,0.00008319343,0.001062706,0.00001057386],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7874734,0.006940777,0.2026123,0.0002666888,0.0001092419,0.0002026647,0.0003457403,0.0009790236,0.001070087],"genre_scores_gemma":[0.6126174,0.005687438,0.3750558,0.0003896497,0.00006404849,0.0001742503,0.002550456,0.0007825296,0.00267852],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00375001,"threshold_uncertainty_score":0.01983219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964188429127252,"score_gpt":0.2942483561696023,"score_spread":0.2746064718783298,"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."}}