{"id":"W2122812051","doi":"10.1093/bioinformatics/btq653","title":"HiTEC: accurate error correction in high-throughput sequencing data","year":2010,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Throughput; DNA sequencing; Source code; Algorithm; Biology; DNA; Genetics","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":[0.0002111237,0.0001269541,0.0001191632,0.00004155372,0.00007325647,0.00003330386,0.0003343611,0.0001287367,0.00000931842],"category_scores_gemma":[0.0001259585,0.0001180049,0.00002447344,0.00008329534,0.00005413779,0.000004901342,0.0003630492,0.0001362021,0.00002424279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001341246,"about_ca_system_score_gemma":0.00008030411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009494205,"about_ca_topic_score_gemma":0.0005458117,"domain_scores_codex":[0.9992427,0.00001047389,0.0002854521,0.0001751327,0.00007915014,0.0002070748],"domain_scores_gemma":[0.9991261,0.00001116118,0.0001065063,0.0006698406,0.00004315518,0.00004320331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007844098,0.00008579563,0.01300563,0.0001027645,0.0001203065,0.000005361801,0.001484964,0.001422582,0.9202802,0.0003950705,0.02231654,0.04070234],"study_design_scores_gemma":[0.004378182,0.0008657739,0.09669942,0.00009982216,0.000131287,0.0003003741,0.005397421,0.2316972,0.2275691,0.0008348823,0.4295568,0.002469703],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942961,0.00009669919,0.001668388,0.0000896753,0.001476123,0.0001510371,0.00008000428,0.000007507679,0.002134477],"genre_scores_gemma":[0.9846901,0.0001147475,0.0143697,0.0002025627,0.0002002859,0.000005756678,0.0002518531,0.00001323133,0.0001517811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6927111,"threshold_uncertainty_score":0.4812101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03351851025080672,"score_gpt":0.2747700612401669,"score_spread":0.2412515509893602,"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."}}