{"id":"W4414116294","doi":"10.1021/acs.analchem.5c01812","title":"A New Approach to Large Multiomics Data Integration","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Cancer Research UK; Department for Business, Energy and Industrial Strategy, UK Government","keywords":"Dimensionality reduction; Data integration; Nonlinear dimensionality reduction; Curse of dimensionality; Reduction (mathematics); Embedding; Data reduction; Sensor fusion; Data transformation","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":[0.00348746,0.001170485,0.001423066,0.003056157,0.0009624024,0.004022751,0.002573768,0.001661732,0.002721587],"category_scores_gemma":[0.006708892,0.0009164643,0.002368928,0.003932022,0.001836279,0.006275303,0.0073631,0.004946934,0.001462479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068564,"about_ca_system_score_gemma":0.001656006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001590644,"about_ca_topic_score_gemma":0.002048546,"domain_scores_codex":[0.9960077,0.0007047319,0.0003044097,0.001221063,0.001594913,0.0001671373],"domain_scores_gemma":[0.9970113,0.0007005617,0.0002077512,0.001164744,0.0007533508,0.0001622048],"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":[0.0003694664,0.0004374846,0.004872371,0.0004784266,0.00067564,0.0007327404,0.0008474129,0.0577487,0.05146402,0.1960598,0.01779888,0.6685151],"study_design_scores_gemma":[0.00003216553,0.0001277515,0.00203873,0.00008070565,0.00009723334,0.000582285,0.0002095223,0.6263458,0.01959816,0.2774845,0.07328904,0.0001141275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002352859,0.0003269509,0.9942328,0.00066508,0.0000972586,0.000050501,0.0002558001,0.001005535,0.001013263],"genre_scores_gemma":[0.04062501,0.0005793492,0.9536768,0.0008742712,0.0002051584,0.0001982383,0.001189793,0.0002705803,0.002380818],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004022751,"threshold_uncertainty_score":0.01844364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03260962697234115,"score_gpt":0.331878856389718,"score_spread":0.2992692294173768,"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."}}