{"id":"W7162040634","doi":"10.1109/iccta68914.2025.11520011","title":"Survey of Emerging Trends in Artificial Intelligence for Bioinformatics","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Applications of artificial intelligence; Field (mathematics); Key (lock); Big data","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001715573,0.0003104509,0.0004640875,0.0006194669,0.00008123701,0.0000493943,0.0004941095,0.0003846001,0.0001130184],"category_scores_gemma":[0.00126712,0.0003172685,0.0001836258,0.001152972,0.0001787297,0.00001100479,0.000292678,0.0002252016,0.000005095934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003619852,"about_ca_system_score_gemma":0.0002607462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002718411,"about_ca_topic_score_gemma":0.001625498,"domain_scores_codex":[0.9971333,0.0001159327,0.001838471,0.0002769144,0.0001632492,0.0004722008],"domain_scores_gemma":[0.9984338,0.0001777386,0.0004290981,0.0005697137,0.0003280789,0.00006153866],"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":[0.0004635307,0.0002925589,0.01796688,0.0009923293,0.0001888811,3.013759e-7,0.0007194759,0.007974349,0.001459699,0.008406973,0.00203872,0.9594963],"study_design_scores_gemma":[0.0004673932,0.0005839208,0.01271452,0.0001974745,0.00006095601,0.000001389738,0.001023429,0.9198577,0.05616018,0.0005842175,0.007784246,0.0005645065],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05878471,0.00100315,0.8900864,0.0007810769,0.001189129,0.0007631785,0.0002969521,0.00002016109,0.04707525],"genre_scores_gemma":[0.9749054,0.0002000336,0.02206082,0.000202455,0.00003804742,0.00001808251,0.0006004679,0.00001809269,0.001956595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9589318,"threshold_uncertainty_score":0.9999279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0275092033924112,"score_gpt":0.3414731639385911,"score_spread":0.3139639605461799,"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."}}