{"id":"W2306172304","doi":"10.1109/tsmcc.2010.2052041","title":"Optimizing Operator–Agent Interaction in Intelligent Adaptive Interface Design: A Conceptual Framework","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University; Defence Research and Development Canada","funders":"","keywords":"Interface (matter); Workload; Sociotechnical system; Computer science; Conceptual design; Systems engineering; User interface; Operator (biology); Control (management); Intelligent agent; Conceptual framework; Human–computer interaction; Knowledge management; Engineering; Artificial intelligence","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":[0.003627292,0.001191724,0.0005126587,0.001446246,0.0008762977,0.004108918,0.002334469,0.002331736,0.002337626],"category_scores_gemma":[0.002946299,0.0006323535,0.000797393,0.0009544829,0.004476042,0.004311411,0.0020668,0.001298767,0.0005766343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001973422,"about_ca_system_score_gemma":0.002735435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003368812,"about_ca_topic_score_gemma":0.002584701,"domain_scores_codex":[0.9980344,0.0009840291,0.0001361649,0.000252438,0.0004584788,0.0001344842],"domain_scores_gemma":[0.9989128,0.0004321962,0.0001710108,0.0001048506,0.0002615037,0.0001176508],"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":[0.00005702734,0.0001983851,0.00119967,0.0005970845,0.000050969,0.0002126685,0.002547967,0.0662113,0.006245114,0.8210951,0.002348097,0.09923662],"study_design_scores_gemma":[0.00009546556,0.0004590915,0.0009519568,0.0006128162,0.0001087391,0.0004055775,0.001858534,0.5379452,0.007821078,0.3851145,0.06452032,0.0001066737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006833093,0.001209713,0.9796566,0.001392695,0.00003601601,0.0001836406,0.00002672399,0.0001913379,0.01047001],"genre_scores_gemma":[0.2138565,0.001750208,0.7791465,0.0002774448,0.00004574201,0.0008716855,0.00008531694,0.00006577095,0.003900738],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004108918,"threshold_uncertainty_score":0.01918316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08370662716168095,"score_gpt":0.3698764251082972,"score_spread":0.2861697979466162,"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."}}