{"id":"W4300689006","doi":"10.1177/11769351221124205","title":"Multi-omics Data Integration Model Based on UMAP Embedding and Convolutional Neural Network","year":2022,"lang":"en","type":"article","venue":"Cancer Informatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Convolutional neural network; Omics; Data integration; Artificial intelligence; Data mining; Machine learning; Bioinformatics; Pattern recognition (psychology); Biology","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":[0.0008330624,0.000931774,0.0006511916,0.00110747,0.000413948,0.0008216297,0.001261368,0.0007242986,0.001002177],"category_scores_gemma":[0.001373292,0.0003998499,0.001097939,0.001219901,0.0004698063,0.001558345,0.0009465597,0.001006197,0.0002819529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001292667,"about_ca_system_score_gemma":0.00124757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01794352,"about_ca_topic_score_gemma":0.01479803,"domain_scores_codex":[0.9995143,0.00008589505,0.0000283676,0.0001923977,0.0001232824,0.00005567592],"domain_scores_gemma":[0.999651,0.0001079264,0.00005865613,0.00004041821,0.0001183999,0.00002364517],"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":[0.0001198054,0.0001043639,0.006372417,0.0001126668,0.0002123847,0.0002591143,0.0001134002,0.8318377,0.005012918,0.01154909,0.002097588,0.1422086],"study_design_scores_gemma":[0.000001156841,0.000008180627,0.0002756067,0.000002528243,0.000007888703,0.0000160197,0.000003193501,0.9973689,0.0004160593,0.001676222,0.000220676,0.000003476099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04395818,0.000639774,0.9515218,0.0005225631,0.00005770835,0.00006944744,0.0004105515,0.001174185,0.001645872],"genre_scores_gemma":[0.8052097,0.000772159,0.1871633,0.000186659,0.00008039865,0.000258831,0.001285026,0.00008659902,0.004957236],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01794352,"threshold_uncertainty_score":0.03567809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03477609712514544,"score_gpt":0.2918279140182447,"score_spread":0.2570518168930992,"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."}}