{"id":"W2159640103","doi":"10.1093/bioinformatics/btq216","title":"Next-generation VariationHunter: combinatorial algorithms for transposon insertion discovery","year":2010,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Genome British Columbia; National Human Genome Research Institute; Howard Hughes Medical Institute","keywords":"Transposable element; Algorithm; Genome; Computer science; Human genome; Structural variation; Scope (computer science); Computational biology; Biology; Genetics; 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":[0.002240058,0.001366737,0.001155644,0.001643991,0.0007545757,0.001326283,0.002949261,0.001692116,0.007899821],"category_scores_gemma":[0.008525358,0.000602495,0.001297047,0.002222667,0.0008961478,0.001393827,0.001363453,0.0020668,0.001499459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009269212,"about_ca_system_score_gemma":0.001656858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003560397,"about_ca_topic_score_gemma":0.004431118,"domain_scores_codex":[0.9989127,0.0004318581,0.00006118237,0.000250875,0.0002594671,0.00008385703],"domain_scores_gemma":[0.9953716,0.003734129,0.0002420106,0.0002643063,0.0002734724,0.0001143895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004931901,0.0002452904,0.003360318,0.0004622463,0.0002542602,0.0002474687,0.0001170488,0.6269032,0.003015629,0.02060449,0.01525601,0.3290408],"study_design_scores_gemma":[0.00007902255,0.00003092237,0.0001418372,0.00001421243,0.00001979979,0.00005773303,0.000009832466,0.9824899,0.001066787,0.01372971,0.002348365,0.00001183969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01249596,0.0006318695,0.9779158,0.0004894799,0.0001005611,0.0001588792,0.0005444766,0.005494369,0.002168444],"genre_scores_gemma":[0.1045551,0.0002151735,0.890883,0.0003665894,0.00008799665,0.0003697463,0.001315772,0.0007758319,0.001430813],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007899821,"threshold_uncertainty_score":0.02642751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02485141532122126,"score_gpt":0.2506231169510057,"score_spread":0.2257717016297844,"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."}}