{"id":"W4311585301","doi":"10.1093/gigascience/giac099","title":"annotate_my_genomes: an easy-to-use pipeline to improve genome annotation and uncover neglected genes by hybrid RNA sequencing","year":2022,"lang":"en","type":"article","venue":"GigaScience","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Research Institute in Oncology and Hematology; CancerCare Manitoba","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Canadian Institutes of Health Research","keywords":"Genome; Annotation; Gene Annotation; Computational biology; Gene; Gene prediction; Genome project; Pipeline (software); Biology; Transcriptome; DNA sequencing; Identification (biology); Exon; Reference genome; Computer science; Genetics; Gene expression","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":[0.00416192,0.003196519,0.001545046,0.00298266,0.002036819,0.00260551,0.003728419,0.00171804,0.01869897],"category_scores_gemma":[0.005704479,0.002432265,0.003084913,0.001921266,0.0006652105,0.002597709,0.003872261,0.004209645,0.01674737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001334045,"about_ca_system_score_gemma":0.002158122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003598934,"about_ca_topic_score_gemma":0.006679452,"domain_scores_codex":[0.9986467,0.0002181153,0.00009225723,0.0005472789,0.0003135924,0.0001820507],"domain_scores_gemma":[0.9983605,0.0006136739,0.0002413633,0.0002935741,0.0002985435,0.0001923896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002598376,0.0003055622,0.009606079,0.003769038,0.00104613,0.0006920045,0.001510301,0.006996934,0.1571548,0.007412539,0.6376167,0.1712916],"study_design_scores_gemma":[0.001107207,0.0004378897,0.02129451,0.0006618611,0.0005818687,0.001438058,0.0004747933,0.09266651,0.138833,0.01968163,0.7220507,0.0007719554],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01631368,0.001175005,0.4138783,0.00105705,0.0007235004,0.0009851548,0.1700585,0.3904594,0.005349275],"genre_scores_gemma":[0.02243109,0.0006639281,0.7123253,0.0008020781,0.0001091582,0.001665086,0.2083836,0.05027308,0.003346765],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01869897,"threshold_uncertainty_score":0.06255424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219868653517652,"score_gpt":0.2297925908934458,"score_spread":0.2175939043582693,"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."}}