{"id":"W4407398500","doi":"10.3934/bioeng.2025004","title":"How artificial intelligence reduces human bias in diagnostics?","year":2025,"lang":"en","type":"article","venue":"AIMS bioengineering","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning","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":[0.0002347881,0.0001330641,0.0002034659,0.0003926408,0.00007177586,0.0000617936,0.00007816907,0.0001110265,0.00003461692],"category_scores_gemma":[0.0009672598,0.0001331159,0.00005134572,0.0005574813,0.00005053515,0.00009821076,0.00002745734,0.0002586951,0.00002304717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001330937,"about_ca_system_score_gemma":0.00009456095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003198885,"about_ca_topic_score_gemma":0.0001134323,"domain_scores_codex":[0.9989513,0.00001652502,0.000367743,0.0002438504,0.0001204686,0.0003001715],"domain_scores_gemma":[0.9993399,0.0002375583,0.00003721746,0.0002179478,0.0000835792,0.00008373037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007471311,0.0006082332,0.04272837,0.0007434966,0.00008100699,0.0001496695,0.003890538,0.00212548,0.07657072,0.09982703,0.001849879,0.7713509],"study_design_scores_gemma":[0.00003705708,0.0002565694,0.01258905,0.00120536,0.00005056586,0.00001681384,0.005061052,0.008945354,0.9411811,0.02755941,0.002724438,0.0003731915],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799717,0.0009125909,0.005895027,0.01116989,0.001019931,0.0003199789,0.000001368869,0.0001089183,0.0006005807],"genre_scores_gemma":[0.9981529,0.0002054726,0.0007650137,0.0002362592,0.0002917728,0.00004324371,0.00001053427,0.00001367564,0.0002811202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8646104,"threshold_uncertainty_score":0.542831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2135824500558615,"score_gpt":0.4180757778556072,"score_spread":0.2044933277997457,"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."}}