{"id":"W2990895847","doi":"10.1101/856591","title":"RepeatModeler2: automated genomic discovery of transposable element families","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":264,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Genome; Annotation; Transposable element; Computational biology; Biology; Identification (biology); Genome project; Genomics; Tree (set theory); Genetics; Computer science; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001654027,0.001929937,0.001043882,0.002029445,0.000753682,0.001319359,0.001910667,0.0009639532,0.006414549],"category_scores_gemma":[0.003398245,0.0008992635,0.001697015,0.001223229,0.0003667789,0.001422123,0.001306614,0.001077523,0.002844668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007443588,"about_ca_system_score_gemma":0.001310944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003484534,"about_ca_topic_score_gemma":0.004362423,"domain_scores_codex":[0.9990637,0.0001589744,0.00004873701,0.0004530375,0.0002182607,0.00005730894],"domain_scores_gemma":[0.9990566,0.0004949619,0.0001154392,0.0001396022,0.0001283847,0.00006495803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004260947,0.0005513842,0.03779264,0.002803548,0.001624582,0.001560175,0.001081287,0.1277562,0.3287843,0.01128299,0.1448167,0.3376852],"study_design_scores_gemma":[0.0003043149,0.0002377436,0.006074083,0.00007489516,0.0001545537,0.0005234105,0.0001443101,0.8320531,0.110764,0.005936014,0.04356698,0.0001664923],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1606143,0.0009367805,0.4753578,0.000459511,0.0001800775,0.0002974388,0.04483358,0.3133569,0.003963619],"genre_scores_gemma":[0.2344601,0.0003308729,0.6783914,0.0002922741,0.00005120077,0.000520313,0.06930049,0.01337704,0.003276267],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006414549,"threshold_uncertainty_score":0.02145886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281386883890619,"score_gpt":0.1962674532148998,"score_spread":0.1834535843759936,"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."}}