{"id":"W4296230867","doi":"10.1145/3557891","title":"The Evolution of HCI and Human Factors: Integrating Human and Artificial Intelligence","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Perspective (graphical); Human intelligence; Computer science; Human–computer interaction; Data science; Engineering ethics; Artificial intelligence; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006671623,0.001169798,0.001228326,0.007488193,0.002264424,0.01100184,0.001530577,0.005449397,0.00388035],"category_scores_gemma":[0.009525499,0.0006537374,0.0006561699,0.007789394,0.01991814,0.01211791,0.003470974,0.005796401,0.0008599677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00623319,"about_ca_system_score_gemma":0.003645833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006445646,"about_ca_topic_score_gemma":0.005389473,"domain_scores_codex":[0.9924241,0.004461183,0.0005589137,0.0007080363,0.001450827,0.000397022],"domain_scores_gemma":[0.9752196,0.02121584,0.0008033615,0.0006535015,0.001506148,0.0006014961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007316386,0.0001126223,0.003736932,0.003702192,0.00009300558,0.0004590188,0.0155132,0.0012259,0.000782278,0.6182134,0.02078586,0.3353025],"study_design_scores_gemma":[0.00001444916,0.000187856,0.005061755,0.00608264,0.00004796881,0.001153388,0.008175471,0.001360542,0.0005288916,0.2528798,0.7243871,0.0001200792],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004159551,0.8724346,0.03390375,0.03975701,0.00323182,0.00007745745,0.00004794513,0.0001444725,0.04624336],"genre_scores_gemma":[0.1529555,0.7572837,0.03704997,0.02648525,0.0104281,0.0004425078,0.00009143299,0.0002064256,0.01505711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01100184,"threshold_uncertainty_score":0.04522514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05269093130983907,"score_gpt":0.3713306980707644,"score_spread":0.3186397667609253,"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."}}