{"id":"W2949158578","doi":"10.1186/s12859-019-2647-2","title":"SplicedFamAlign: CDS-to-gene spliced alignment and identification of transcript orthology groups","year":2019,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Exon; RNA splicing; Intron; Biology; Genetics; Gene; Computational biology; Sequence alignment; Alternative splicing; Genome; DNA microarray; Gene prediction; Sequence analysis; Alignment-free sequence analysis; Peptide sequence; Gene expression; RNA","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000208172,0.000140244,0.0001906485,0.00005448605,0.00003925136,0.00001466842,0.0001444153,0.0001038624,0.000006205903],"category_scores_gemma":[0.00001663384,0.0001326295,0.00006187132,0.00007231875,0.00005124357,0.000001995871,0.0001052416,0.00003134432,0.00002929638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006945142,"about_ca_system_score_gemma":0.00002899115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006655726,"about_ca_topic_score_gemma":0.00001597372,"domain_scores_codex":[0.9990569,0.000018337,0.0004536795,0.0001812374,0.0001048542,0.000184937],"domain_scores_gemma":[0.9993293,0.00001073452,0.0001566517,0.0003677513,0.00006801706,0.0000675781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004581311,0.00002633037,0.009976255,0.0001316093,0.00004851089,9.669552e-8,0.0006620171,0.0002546965,0.9874237,0.0004581484,0.0001374382,0.0008354124],"study_design_scores_gemma":[0.001424098,0.0008562656,0.1141957,0.00002188665,0.00008437589,0.00003301162,0.00180575,0.00259298,0.8686486,0.0001763658,0.009667172,0.0004938287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857392,0.0003228653,0.01255676,0.00005137342,0.0001960406,0.0004128529,0.00005858444,0.000003591967,0.0006587089],"genre_scores_gemma":[0.9806716,0.0002240881,0.01849116,0.0002285652,0.00004100786,0.00001990257,0.00004966119,0.00001309378,0.0002609527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1187751,"threshold_uncertainty_score":0.5408474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001318829358899,"score_gpt":0.2244768345254669,"score_spread":0.2144636462318779,"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."}}