{"id":"W4399679431","doi":"10.1038/s41592-024-02299-2","title":"The tidyomics ecosystem: enhancing omic data analyses","year":2024,"lang":"en","type":"article","venue":"Nature Methods","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bioconductor; Software; Computer science; Ecosystem; Data integration; Data science; Biology; Ecology; Data mining","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":[0.006192981,0.0009801165,0.0008204327,0.002837239,0.001090735,0.004157977,0.001139442,0.0009216781,0.003477892],"category_scores_gemma":[0.009548732,0.0007591202,0.001362876,0.002169749,0.0005069011,0.003250604,0.005197619,0.001540315,0.002019048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006252988,"about_ca_system_score_gemma":0.00175733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00373462,"about_ca_topic_score_gemma":0.01723779,"domain_scores_codex":[0.9982488,0.0003838764,0.0001603863,0.0005425963,0.0005304214,0.000133974],"domain_scores_gemma":[0.9947224,0.001476254,0.0004158894,0.001461562,0.001065256,0.0008588164],"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":[0.002185654,0.0004905241,0.2596042,0.003330183,0.003650127,0.001446121,0.003252076,0.00940786,0.3427729,0.01102532,0.09275492,0.2700802],"study_design_scores_gemma":[0.00047863,0.0003396365,0.2929542,0.0009670398,0.001336642,0.001638637,0.002047536,0.08021922,0.0776985,0.04356768,0.4982187,0.0005336739],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.397379,0.006493742,0.2601745,0.00911495,0.002038271,0.0006681895,0.2306922,0.07123393,0.0222052],"genre_scores_gemma":[0.2672873,0.002318582,0.6056358,0.002484768,0.0005295931,0.0003938735,0.1085301,0.009728828,0.003091244],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006192981,"threshold_uncertainty_score":0.03275204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07161139240283616,"score_gpt":0.4571858991353127,"score_spread":0.3855745067324766,"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."}}