{"id":"W4402956412","doi":"10.18280/mmep.110910","title":"Investigation of Machine Learning on Gene Expression Data for Cancer Detection","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Gene expression; Computational biology; Gene; Computer science; Artificial intelligence; Machine learning; Biology; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005121,0.0004002166,0.0007591419,0.001132875,0.000321329,0.001261843,0.0007764472,0.0007330097,0.0009774361],"category_scores_gemma":[0.01929739,0.0002118518,0.0006980315,0.001292629,0.0009574695,0.00129821,0.0004152424,0.001134899,0.0001886614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110846,"about_ca_system_score_gemma":0.0008376657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164132,"about_ca_topic_score_gemma":0.001006878,"domain_scores_codex":[0.9983543,0.0008657558,0.00007766001,0.0001879118,0.0004258245,0.00008849863],"domain_scores_gemma":[0.9762648,0.02154175,0.0005570187,0.0005822189,0.0009441094,0.0001101883],"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":[0.000482166,0.0005051775,0.0329098,0.0005220125,0.0001957577,0.0003235792,0.0002962256,0.6403372,0.01620442,0.0608119,0.001801648,0.24561],"study_design_scores_gemma":[0.000004322262,0.00004475551,0.003093939,0.0000117262,0.000008751116,0.00008690491,0.00003940168,0.9807262,0.003274644,0.01217917,0.000523351,0.000006848513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5439397,0.00293509,0.4457578,0.002683721,0.00007159203,0.0000770365,0.00046653,0.0003946455,0.003674069],"genre_scores_gemma":[0.9424471,0.0006342027,0.0546909,0.0001115941,0.00006305098,0.00004295675,0.0004322835,0.00002978999,0.001548093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005121,"threshold_uncertainty_score":0.0270828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05230812706575685,"score_gpt":0.2619563921344277,"score_spread":0.2096482650686708,"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."}}