{"id":"W4411487526","doi":"10.2196/70709","title":"Stacked Deep Learning Ensemble for Multiomics Cancer Type Classification: Development and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"AI in cancer detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Ensemble learning; Artificial intelligence; Computer science; Machine learning; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000176762,0.00009414195,0.0001151165,0.0002140838,0.0002400963,0.00009502082,0.0001677173,0.00016295,6.231053e-7],"category_scores_gemma":[0.0000298227,0.00008660979,0.000009379793,0.0003637346,0.00004662475,0.0001845141,0.0001689365,0.0001227048,0.000001781271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008092187,"about_ca_system_score_gemma":0.00006994217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006034806,"about_ca_topic_score_gemma":0.00003525163,"domain_scores_codex":[0.9993532,0.00001097497,0.0002529694,0.0001752955,0.00006730632,0.0001403068],"domain_scores_gemma":[0.9995464,0.00003961867,0.000124272,0.0001764857,0.00009274489,0.00002044787],"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":[0.00001672655,0.00003646209,0.001599523,0.00008756657,0.00003478071,1.536625e-7,0.001790808,0.00003731095,0.001325323,0.008746552,0.00006937783,0.9862554],"study_design_scores_gemma":[0.001415413,0.0005223275,0.007961403,0.00004454798,0.00002182928,0.000006291354,0.003203009,0.8811348,0.04832369,0.00116745,0.05589714,0.0003021141],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3806205,0.0001181298,0.6168966,0.001221127,0.000221651,0.0006789341,6.945905e-7,0.0001680338,0.00007435232],"genre_scores_gemma":[0.8770627,0.0002203507,0.1222661,0.0000918925,0.00001147735,0.0002147917,0.000005169567,0.000004577377,0.000122951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9859533,"threshold_uncertainty_score":0.3531845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609775852585585,"score_gpt":0.3031101957100789,"score_spread":0.277012437184223,"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."}}