{"id":"W2108563376","doi":"10.1093/bioinformatics/btq639","title":"TE Displayer for post-genomic analysis of transposable elements","year":2010,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transposable element; In silico; Computer science; Computational biology; Biology; Data mining; Artificial intelligence; Genome; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00009249226,0.00006158303,0.0001269404,0.00001952804,0.00008272576,0.00001756029,0.0001346975,0.00004881439,0.0004586649],"category_scores_gemma":[0.00001848688,0.00002342204,0.0001408963,0.0002888904,0.00001906331,0.00006083238,0.00001383905,0.00003358732,0.00001191509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003724217,"about_ca_system_score_gemma":0.00000721842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003088271,"about_ca_topic_score_gemma":0.002253257,"domain_scores_codex":[0.9994516,0.000003317239,0.0002782566,0.00005720908,0.00008428744,0.0001253802],"domain_scores_gemma":[0.9996686,0.00006775007,0.00009929022,0.0000476274,0.0000723081,0.00004441044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004019783,0.0002007025,0.1074534,0.00004414996,0.0005611067,1.219022e-7,0.001091972,0.0000887222,0.7917381,0.003499848,0.0002305134,0.09505114],"study_design_scores_gemma":[0.0005411245,0.0005143488,0.7867675,0.000008493444,0.001159727,0.000001685473,0.0009431081,0.1241287,0.01710569,0.0005746328,0.06787249,0.0003824566],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980896,0.000005268331,0.00006310225,0.0002490835,0.00008201283,0.0001732425,0.0009038807,0.00001186008,0.0004219715],"genre_scores_gemma":[0.9937851,0.000004054604,0.005477678,0.0001161843,0.0000403922,0.00001059307,0.0004677494,3.441815e-7,0.00009785923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7746324,"threshold_uncertainty_score":0.5022059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01288665588595654,"score_gpt":0.2227007248534885,"score_spread":0.209814068967532,"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."}}