{"id":"W4309383133","doi":"10.1101/2022.11.14.516459","title":"MOT: a Multi-Omics Transformer for multiclass classification tumour types predictions","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre; Université Laval","funders":"Compute Canada","keywords":"Omics; Epigenomics; Computer science; Computational biology; Proteomics; Machine learning; Biology; Bioinformatics; Artificial intelligence; DNA methylation; 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":[0.00178028,0.001121023,0.000694111,0.001130987,0.0003051795,0.0009177961,0.001338339,0.00110083,0.002577552],"category_scores_gemma":[0.003337951,0.0003764157,0.00151472,0.0005858765,0.0003794891,0.0009849238,0.001408726,0.001380065,0.000895332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001126049,"about_ca_system_score_gemma":0.001078326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006212048,"about_ca_topic_score_gemma":0.006892375,"domain_scores_codex":[0.9995874,0.0001222702,0.00002473935,0.0001193744,0.00008965121,0.0000566225],"domain_scores_gemma":[0.9992833,0.0003626427,0.00006979693,0.00007051798,0.0001580249,0.00005575113],"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":[0.001094409,0.0003110422,0.03194394,0.0003316554,0.0006077298,0.0004099124,0.0001665898,0.6459424,0.01187733,0.007918523,0.0140685,0.2853279],"study_design_scores_gemma":[0.00001208903,0.00004833707,0.0006726537,0.00001353362,0.00002785656,0.00004490689,0.00001205534,0.9922003,0.001529652,0.004571829,0.000857469,0.000009284603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.130776,0.001551569,0.845215,0.002254455,0.0002143883,0.0002777703,0.005261263,0.01092102,0.003528593],"genre_scores_gemma":[0.8311124,0.000502811,0.157133,0.0008957259,0.00008946857,0.0002979531,0.005584536,0.0002805014,0.004103689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006212048,"threshold_uncertainty_score":0.01235181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0208029644221978,"score_gpt":0.2478257571152471,"score_spread":0.2270227926930493,"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."}}