{"id":"W2018041181","doi":"10.1371/journal.pone.0102398","title":"JAGuaR: Junction Alignments to Genome for RNA-Seq Reads","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"National Institutes of Health; Genome British Columbia; National Cancer Institute; BC Cancer Foundation; Genome Canada","keywords":"Exon; Genome; Jaguar; Computational biology; Biology; Genetics; Reference genome; RNA-Seq; Transcriptome; Gene; 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":[0.003485433,0.002631609,0.002264059,0.00294178,0.001969428,0.002808255,0.003336752,0.00196078,0.0260568],"category_scores_gemma":[0.008181682,0.002781003,0.002037374,0.002657084,0.0006483198,0.001830745,0.002598432,0.006005218,0.03021233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007101345,"about_ca_system_score_gemma":0.001231228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007713509,"about_ca_topic_score_gemma":0.001971383,"domain_scores_codex":[0.9969622,0.0007859105,0.0003378632,0.001128051,0.0005638934,0.0002219815],"domain_scores_gemma":[0.9983389,0.0006649571,0.0002305915,0.0003833595,0.0002753548,0.0001066606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003524113,0.0003931316,0.004972472,0.005997631,0.001280414,0.001264071,0.002311667,0.005189625,0.4767973,0.02050347,0.2984721,0.1792939],"study_design_scores_gemma":[0.0005400118,0.0006135851,0.008343436,0.0005975134,0.000362821,0.001691809,0.0004591521,0.05307654,0.3177837,0.02105068,0.5949619,0.0005188238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0137491,0.001560839,0.6636618,0.0001949242,0.001030547,0.000868847,0.04930232,0.2622073,0.007424254],"genre_scores_gemma":[0.03011775,0.0005088504,0.8170457,0.0003664445,0.0001211511,0.002198042,0.08302602,0.06251901,0.004096986],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0260568,"threshold_uncertainty_score":0.08716869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02912166422205615,"score_gpt":0.2226575998183369,"score_spread":0.1935359355962808,"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."}}