{"id":"W2624702742","doi":"10.1101/149864","title":"LIONS: Analysis Suite for Detecting and Quantifying Transposable Element Initiated Transcription from RNA-seq","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Terry Fox Research Institute; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Transposable element; RNA-Seq; Suite; Container (type theory); Computer science; Transcriptome; Source code; Computational biology; Transcription (linguistics); Biology; Genetics; Genome; Gene; Gene expression; Geography; Programming language; Engineering","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":[0.005228482,0.003171163,0.001931455,0.00263877,0.001139698,0.002853473,0.002489435,0.001068572,0.02754418],"category_scores_gemma":[0.006165894,0.001806629,0.001890884,0.001602755,0.0008841563,0.001443672,0.002038332,0.003302742,0.01698989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001219813,"about_ca_system_score_gemma":0.002581112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002116763,"about_ca_topic_score_gemma":0.003909608,"domain_scores_codex":[0.997709,0.0004109895,0.0002502128,0.0007247588,0.0007076174,0.0001972739],"domain_scores_gemma":[0.997366,0.001459687,0.0003375456,0.000317947,0.0003641,0.0001547157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002851855,0.0002595517,0.01172011,0.007108427,0.00130442,0.0009906995,0.001600599,0.01322295,0.2564086,0.01982717,0.560066,0.1246396],"study_design_scores_gemma":[0.001021489,0.0006882339,0.02790679,0.0008178847,0.0005879185,0.001171857,0.0003898179,0.1648188,0.3193946,0.03602141,0.446339,0.0008421019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01344855,0.0006988073,0.3974977,0.000343799,0.0002485069,0.0008504005,0.2052444,0.3753316,0.006336369],"genre_scores_gemma":[0.04790093,0.0005810532,0.6346009,0.001228419,0.0001398524,0.007203905,0.2115069,0.08827564,0.008562366],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02754418,"threshold_uncertainty_score":0.09214443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06268787555715599,"score_gpt":0.255676011201434,"score_spread":0.192988135644278,"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."}}