{"id":"W3138924738","doi":"10.1101/gr.269894.120","title":"Ultrafast functional profiling of RNA-seq data for nonmodel organisms","year":2021,"lang":"en","type":"article","venue":"Genome Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Genome Canada","keywords":"Biology; Bottleneck; Sequence assembly; Computational biology; RNA-Seq; Pipeline (software); Reference genome; Computer science; Workflow; DNA sequencing; Gene; Data mining; Transcriptome; Genetics; Database; Programming language","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":[0.0007065412,0.00008669831,0.0001320755,0.00004130824,0.00015471,0.00002580199,0.0003502161,0.00008088939,0.00003668726],"category_scores_gemma":[0.000239848,0.0000857909,0.00004984506,0.0001380421,0.0001080386,9.949154e-7,0.0006554064,0.00009073322,0.000005131244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001231342,"about_ca_system_score_gemma":0.0004182105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009706439,"about_ca_topic_score_gemma":0.00001904554,"domain_scores_codex":[0.99876,0.00005665109,0.0001812642,0.0004555752,0.0002239738,0.0003224894],"domain_scores_gemma":[0.998481,0.00004883839,0.00003318522,0.0007408705,0.0006338292,0.00006222085],"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":[0.00005529807,0.00005533656,0.0004945816,0.00005343705,0.00009740188,0.000001169479,0.00002661394,0.0001989631,0.9979596,0.0003269098,0.000286737,0.000444024],"study_design_scores_gemma":[0.0004517479,0.000174306,0.002363924,0.000004630368,0.00001209942,0.000009448946,0.0003548146,0.0001957252,0.9698406,0.0005410252,0.02593037,0.0001212816],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812596,0.002641211,0.01301877,0.0002567973,0.0001231896,0.0003141276,0.001236594,0.00000158894,0.00114811],"genre_scores_gemma":[0.9879016,0.0006900761,0.007930638,0.00003368409,0.0004058557,0.00003707006,0.001390471,0.00002484145,0.001585714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0281189,"threshold_uncertainty_score":0.3498451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.172815722806266,"score_gpt":0.3674804413055738,"score_spread":0.1946647184993078,"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."}}