{"id":"W4413835134","doi":"10.1177/10711813251367751","title":"Augmented Cognition Meets AI: Enhancing Human Performance with Real-Time, Adaptive, and Trustworthy Intelligence","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Justice Canada; Division of Information and Intelligent Systems; U.S. Department of Justice; National Science Foundation","keywords":"Trustworthiness; Cognition; Computer science; Artificial intelligence; Cognitive science; Psychology; Computer security; Neuroscience","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.003110519,0.0009466417,0.0003776053,0.0006472293,0.001361886,0.006136856,0.001133081,0.001822311,0.01075098],"category_scores_gemma":[0.003659328,0.0003085571,0.0006084139,0.0003390724,0.003298565,0.005115306,0.004744168,0.00154528,0.001927484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008694354,"about_ca_system_score_gemma":0.001340658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007545041,"about_ca_topic_score_gemma":0.001499811,"domain_scores_codex":[0.9980693,0.0010208,0.00007605244,0.0001789816,0.0004714156,0.0001834293],"domain_scores_gemma":[0.998047,0.001004423,0.0001031763,0.000232061,0.0003602129,0.0002530713],"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":[0.0004996565,0.0004422856,0.004567426,0.001147118,0.0001899888,0.0002890798,0.01083466,0.00762695,0.02146209,0.1350109,0.07373418,0.7441958],"study_design_scores_gemma":[0.0001132546,0.001295723,0.00940474,0.001033088,0.0002296603,0.0005796886,0.008009332,0.01785441,0.01413564,0.1936617,0.7535031,0.0001797412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09268154,0.02024225,0.3577971,0.07270209,0.004030997,0.0006116556,0.0002120972,0.003691569,0.4480307],"genre_scores_gemma":[0.8075013,0.01252608,0.1178888,0.006238739,0.001563704,0.0005613996,0.0002460639,0.0003666079,0.05310738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01075098,"threshold_uncertainty_score":0.03596562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436949509294249,"score_gpt":0.2837413808911979,"score_spread":0.2693718857982554,"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."}}