{"id":"W4302022996","doi":"10.1101/2022.10.02.510482","title":"A Protocol for Single Nucleus RNAseq from Frozen Skeletal Muscle","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research; Cumming School of Medicine, University of Calgary; University of Calgary","keywords":"Skeletal muscle; Multinucleate; Nucleus; Biology; RNA; Cell; Myocyte; Cell biology; Computational biology; Bioinformatics; Anatomy; Gene; Genetics","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":[0.002391673,0.002722395,0.001764766,0.002656739,0.00191877,0.00102619,0.002811303,0.001173485,0.04204717],"category_scores_gemma":[0.002006864,0.002159795,0.001398801,0.001773764,0.001059862,0.0006889116,0.001796891,0.004264392,0.04729616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006152872,"about_ca_system_score_gemma":0.001955861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008418912,"about_ca_topic_score_gemma":0.002260478,"domain_scores_codex":[0.9978618,0.0003961771,0.000312979,0.0006686869,0.0005199439,0.0002404066],"domain_scores_gemma":[0.9987084,0.0002755689,0.00005333463,0.000558145,0.0003080257,0.00009662104],"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":[0.0004324823,0.0002202907,0.0006509619,0.001630376,0.0001635654,0.001525968,0.0005252365,0.001180292,0.8625602,0.01012604,0.06052421,0.06046028],"study_design_scores_gemma":[0.0002700375,0.000442181,0.003552841,0.0003438688,0.0001252216,0.001728777,0.00008760032,0.003618735,0.3283597,0.009093698,0.6521605,0.0002169655],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.007878289,0.001835685,0.9411227,0.0004469492,0.001169218,0.006879683,0.01824422,0.008719805,0.0137034],"genre_scores_gemma":[0.02121678,0.002201923,0.8563651,0.000847242,0.0003080336,0.02334672,0.0580962,0.004354666,0.03326332],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.04204717,"threshold_uncertainty_score":0.1406618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920818860376941,"score_gpt":0.255483491394899,"score_spread":0.2362753027911295,"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."}}