{"id":"W4403039748","doi":"10.1186/s12859-024-05935-y","title":"ScRNAbox: empowering single-cell RNA sequencing on high performance computing systems","year":2024,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Montreal Neurological Institute and Hospital; Fondation Brain Canada; McGill University; Canadian Institutes of Health Research; Québec Consortium for Drug Discovery; Michael J. Fox Foundation for Parkinson's Research","keywords":"Computer science; Scalability; Workstation; Pipeline (software); Workload; Distributed computing; Cluster analysis; Database; Operating system","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":[0.003747599,0.001276193,0.001046655,0.0009704531,0.001072378,0.00217785,0.002416791,0.001237079,0.0108724],"category_scores_gemma":[0.006235884,0.001081018,0.001317819,0.0007143152,0.0008636552,0.002224701,0.003116027,0.002227094,0.00952698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006281811,"about_ca_system_score_gemma":0.001504066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001115315,"about_ca_topic_score_gemma":0.00241622,"domain_scores_codex":[0.9976754,0.0004578207,0.000148677,0.0006538294,0.0008650598,0.0001992206],"domain_scores_gemma":[0.9968975,0.001232499,0.0002182813,0.0006230186,0.0006231256,0.0004056097],"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":[0.003386015,0.0003626928,0.008250381,0.002529373,0.0005597895,0.001274715,0.001302399,0.02058402,0.518575,0.01434809,0.1857825,0.2430451],"study_design_scores_gemma":[0.0005309976,0.0006489089,0.006399641,0.0004089109,0.0001714771,0.0007544335,0.000301439,0.2678211,0.4441467,0.02745949,0.2508041,0.0005528404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.03938774,0.001373177,0.7245098,0.001311567,0.0009520799,0.0006298387,0.008087956,0.2165136,0.007234261],"genre_scores_gemma":[0.1239218,0.001462899,0.8215655,0.001726892,0.0003327034,0.001418763,0.01981691,0.02289877,0.006855695],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0108724,"threshold_uncertainty_score":0.03637177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338978764892393,"score_gpt":0.2303998211280654,"score_spread":0.2070100334791415,"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."}}