{"id":"W4386023237","doi":"10.1101/2023.08.18.553919","title":"mosaicMPI: a framework for modular data integration across cohorts and -omics modalities","year":2023,"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":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Alberta Children's Hospital Foundation; Children's Hospital Foundation; American College Health Foundation; Alberta Children's Hospital Research Institute; Terry Fox Research Institute","keywords":"Computer science; Modular design; Modalities; Profiling (computer programming); Data integration; Data science; Biological network; Computational biology; Data mining; Biology","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":[0.01477338,0.002456459,0.002758029,0.004862318,0.001676674,0.006342344,0.005543683,0.001781412,0.01026327],"category_scores_gemma":[0.02264501,0.003268249,0.006536398,0.005253409,0.001798401,0.004236547,0.01278875,0.004970101,0.003840005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001778773,"about_ca_system_score_gemma":0.004316989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008967417,"about_ca_topic_score_gemma":0.01349038,"domain_scores_codex":[0.9969013,0.0009275809,0.00033287,0.0008624182,0.0007752379,0.0002006511],"domain_scores_gemma":[0.9943424,0.002631856,0.0004752667,0.001570311,0.0005024227,0.0004775411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002589412,0.0003106255,0.01588797,0.006118481,0.005679064,0.002533707,0.004633957,0.1149037,0.03114037,0.2215936,0.2116944,0.3829147],"study_design_scores_gemma":[0.0003759158,0.0001888665,0.00567499,0.0007247722,0.0005505516,0.0008257785,0.0004408623,0.4320788,0.01424523,0.3624611,0.1820262,0.0004069979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001424919,0.0004373539,0.9195517,0.0004190224,0.00009254141,0.0002493641,0.0139121,0.06305809,0.0008549178],"genre_scores_gemma":[0.02549601,0.0005413667,0.9347233,0.0004284422,0.0001164536,0.001513023,0.02665769,0.009704083,0.0008194937],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01477338,"threshold_uncertainty_score":0.07812995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04616002649427174,"score_gpt":0.2786364171014342,"score_spread":0.2324763906071625,"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."}}