{"id":"W4200475779","doi":"10.1016/j.mlwa.2021.100225","title":"Alzheimer’s disease diagnosis using genetic programming based on higher order spectra features","year":2021,"lang":"en","type":"article","venue":"Machine Learning with Applications","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Genetic programming; Computer science; Artificial intelligence; Machine learning; Disease; Linear discriminant analysis; Set (abstract data type); Computer-aided diagnosis; Field (mathematics); Pattern recognition (psychology); Medicine; Pathology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009662528,0.0002690923,0.0001627134,0.00006887654,0.0003728163,0.0001073268,0.0002047704,0.00009926879,0.000147369],"category_scores_gemma":[0.0001099475,0.0002401709,0.00008083603,0.0004033739,0.00008830186,0.000005134542,0.00008419857,0.0004001115,0.00002491862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002197576,"about_ca_system_score_gemma":0.0001815848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003589092,"about_ca_topic_score_gemma":0.00002352889,"domain_scores_codex":[0.998606,0.0001117823,0.0002216143,0.0004712446,0.0002584313,0.00033088],"domain_scores_gemma":[0.9988161,0.00004816896,0.0001569256,0.000632118,0.0001557309,0.0001909694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001845895,0.0005576792,0.3902928,0.0001213424,0.0002205765,0.00003338901,0.00006296881,0.570916,0.00273721,0.000845728,0.0005751876,0.03345253],"study_design_scores_gemma":[0.001506672,0.0005114487,0.1341784,0.0001075101,0.0004925719,0.00005463796,0.00004386457,0.108839,0.006245454,0.00005266401,0.7468975,0.001070227],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1949786,0.01182992,0.7649357,0.009845699,0.0003121652,0.004307824,0.0001752542,0.0008584465,0.01275631],"genre_scores_gemma":[0.7653973,0.00006039816,0.2301116,0.001170421,0.0003408483,0.0007028055,0.001134257,0.0001079475,0.0009744584],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7463223,"threshold_uncertainty_score":0.9793885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060703576292461,"score_gpt":0.2680442803859967,"score_spread":0.2574372446230721,"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."}}