{"id":"W4213175660","doi":"10.1101/2022.02.18.481000","title":"ERROR MODELLED GENE EXPRESSION ANALYSIS (EMOGEA) PROVIDES A SUPERIOR OVERVIEW OF TIME COURSE RNA-SEQ MEASUREMENTS AND LOW COUNT GENE EXPRESSION","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital Research Institute of Manitoba; Dalhousie University","funders":"","keywords":"RNA-Seq; Computational biology; Gene expression; RNA; Biology; Gene; Expression (computer science); Computer science; Genetics; Transcriptome","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004028653,0.001417922,0.00111359,0.001307872,0.000405225,0.001650079,0.001430095,0.001178583,0.001459045],"category_scores_gemma":[0.005756002,0.000462496,0.001912489,0.001046769,0.001214354,0.0008460121,0.001361838,0.002840578,0.0005776652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007669624,"about_ca_system_score_gemma":0.001092785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001371149,"about_ca_topic_score_gemma":0.001650015,"domain_scores_codex":[0.9982777,0.0005984495,0.00009485724,0.0004942325,0.0004495017,0.00008536456],"domain_scores_gemma":[0.9958354,0.002538013,0.0005070428,0.0007214646,0.0003213608,0.00007669041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004478897,0.000228487,0.01360447,0.001155901,0.0008400403,0.0005882805,0.0004952439,0.4411408,0.2932003,0.0911282,0.003066886,0.1541036],"study_design_scores_gemma":[0.00002010798,0.000165504,0.005951738,0.00006710148,0.00009622629,0.0002535305,0.00007466361,0.8701999,0.05779008,0.05293071,0.01234908,0.0001013484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006857084,0.0002028409,0.9914258,0.00007485222,0.00002684725,0.00002757882,0.0003570819,0.0006806522,0.0003473997],"genre_scores_gemma":[0.2361396,0.0006115717,0.7585619,0.0003516658,0.00009354204,0.0004515979,0.001614987,0.0008379539,0.001337165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004028653,"threshold_uncertainty_score":0.0213058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03176370461937417,"score_gpt":0.2459518657017,"score_spread":0.2141881610823259,"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."}}