{"id":"W2054856719","doi":"10.1186/1756-0500-3-185","title":"Optimus Primer: A PCR enrichment primer design program for next-generation sequencing of human exonic regions","year":2010,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute; Université de Montréal","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Institut de Cardiologie de Montréal; Crohn's and Colitis Foundation; Genome Canada; Crohn's and Colitis Foundation of America","keywords":"Amplicon; Primer (cosmetics); Computational biology; Context (archaeology); Polymerase chain reaction; Genetics; Human genome; Computer science; Gene; Exon; Genome; Biology","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":[0.002382955,0.002026951,0.001032725,0.001324822,0.0006108895,0.000904205,0.001452231,0.001071837,0.01107895],"category_scores_gemma":[0.002756117,0.001684137,0.001469426,0.0006275851,0.0006853859,0.0008360409,0.001195349,0.00222378,0.007152778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005200608,"about_ca_system_score_gemma":0.001438225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005278853,"about_ca_topic_score_gemma":0.001184063,"domain_scores_codex":[0.9984559,0.0003667906,0.0001645808,0.0004680498,0.0004258727,0.0001187377],"domain_scores_gemma":[0.9989329,0.0006381616,0.0001796471,0.00006580898,0.0001312284,0.00005219197],"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":[0.004262045,0.0003862815,0.005605687,0.003744478,0.0005408736,0.0008077742,0.0009731901,0.01737711,0.5229787,0.00713433,0.06865766,0.3675319],"study_design_scores_gemma":[0.0007165432,0.00082816,0.004079629,0.0003971823,0.0003676817,0.002290355,0.0001197856,0.157658,0.626923,0.007487559,0.1988257,0.0003063422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01648733,0.001187798,0.9043786,0.0001981726,0.0001522788,0.0005344065,0.005287447,0.06911039,0.002663667],"genre_scores_gemma":[0.01646077,0.0003031789,0.9710579,0.0002313124,0.00001923579,0.00120037,0.003540434,0.004701437,0.002485387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01107895,"threshold_uncertainty_score":0.03706276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2971795323488539,"score_gpt":0.4440941810489369,"score_spread":0.146914648700083,"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."}}