{"id":"W4213143350","doi":"10.21203/rs.3.rs-1348696/v1","title":"MOT: a Multi-Omics Transformer for Multiclass Classification Tumour Types Predictions","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Omics; Epigenomics; Interpretability; Computer science; Metabolomics; Proteomics; Computational biology; Data type; Machine learning; Bioinformatics; Biology; DNA methylation; Gene","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":[0.001772629,0.001683882,0.0008907197,0.00213433,0.000716584,0.002080222,0.001408461,0.001450038,0.02570029],"category_scores_gemma":[0.006255901,0.0006580537,0.002353003,0.001603713,0.0004307934,0.002720186,0.002795199,0.001543564,0.01240321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008089554,"about_ca_system_score_gemma":0.0009506512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001833361,"about_ca_topic_score_gemma":0.002943072,"domain_scores_codex":[0.9991264,0.0001298212,0.00005879029,0.0002826243,0.000290626,0.0001117058],"domain_scores_gemma":[0.9986417,0.0006170741,0.00006454481,0.0003284904,0.0002555349,0.00009271815],"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":[0.004553173,0.0003984499,0.01680828,0.001996711,0.0007106474,0.0008161327,0.0004451371,0.0232152,0.05934427,0.03536881,0.333767,0.5225761],"study_design_scores_gemma":[0.0003596303,0.0003265063,0.01227609,0.0003063182,0.0003359698,0.001254059,0.0003362772,0.5617306,0.09676085,0.1430708,0.1830593,0.0001835056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0178701,0.0006083464,0.723487,0.001435178,0.0008166184,0.0002934397,0.08549953,0.162063,0.007926763],"genre_scores_gemma":[0.2225948,0.0007312288,0.6417908,0.001559357,0.0004340919,0.0006582116,0.1010255,0.01480729,0.01639876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02570029,"threshold_uncertainty_score":0.08597606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0857513674605884,"score_gpt":0.3999089199837702,"score_spread":0.3141575525231818,"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."}}