{"id":"W4308527150","doi":"10.21203/rs.3.rs-2187066/v1","title":"A unified platform for RNA-seq analysis in non-model species","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Environment and Climate Change Canada","funders":"Government of Canada; Génome Québec; Genome Canada","keywords":"RNA-Seq; Computational biology; Computer science; Biology; Genetics; 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":[0.006010563,0.002212695,0.001753118,0.002428019,0.0008909887,0.0024266,0.003271752,0.001169219,0.007561494],"category_scores_gemma":[0.005232099,0.001563788,0.001746648,0.001634573,0.0009063304,0.00163731,0.003123656,0.002865992,0.009953085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006328459,"about_ca_system_score_gemma":0.00208188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001566393,"about_ca_topic_score_gemma":0.002543207,"domain_scores_codex":[0.9969839,0.0005103254,0.0003799557,0.0006862213,0.00122885,0.0002106123],"domain_scores_gemma":[0.9970908,0.0008613791,0.0002725599,0.0009859824,0.000526929,0.0002623289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001887304,0.0006910865,0.006428713,0.001665433,0.001249342,0.001661718,0.0008825518,0.01860544,0.5809011,0.02228114,0.1873277,0.1764185],"study_design_scores_gemma":[0.0007352663,0.0004834984,0.01349141,0.0003252891,0.0003630254,0.001668518,0.0001618603,0.2120935,0.4004834,0.03328996,0.3362284,0.0006758246],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00713428,0.0002233969,0.7895672,0.0001574059,0.0002198991,0.0003739782,0.02108432,0.178985,0.002254596],"genre_scores_gemma":[0.03130187,0.0003293018,0.8533613,0.000487318,0.0001117001,0.002809482,0.07298204,0.03423538,0.004381652],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.007561494,"threshold_uncertainty_score":0.03178728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08401813426610957,"score_gpt":0.3806335261651395,"score_spread":0.2966153918990299,"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."}}