{"id":"W4383616954","doi":"10.1007/978-3-031-35389-5_22","title":"A Framework for Supporting Adaptive Human-AI Teaming in Air Traffic Control","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"International Air Transport Association","funders":"","keywords":"Air traffic control; Computer science; Operationalization; Context (archaeology); Set (abstract data type); Control (management); Human-in-the-loop; Artificial intelligence; Human–computer interaction; 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":[0.001059382,0.0005703587,0.0005125172,0.0004865899,0.00136803,0.002498417,0.002783338,0.001532987,0.006580071],"category_scores_gemma":[0.001576111,0.0004953445,0.0008350565,0.0004311738,0.001592659,0.00204259,0.003143009,0.00175749,0.0015629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007383965,"about_ca_system_score_gemma":0.001540475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008350671,"about_ca_topic_score_gemma":0.008892591,"domain_scores_codex":[0.9993653,0.000157763,0.00004379656,0.0001247191,0.0001920878,0.0001164329],"domain_scores_gemma":[0.9996302,0.0001312801,0.00002351098,0.00007474911,0.00006442646,0.00007585596],"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":[0.0001437083,0.0002233252,0.0006461421,0.0002340341,0.00006704091,0.0004484514,0.001195767,0.1218191,0.01260078,0.701026,0.009063635,0.152532],"study_design_scores_gemma":[0.00005210976,0.0001048205,0.0002312036,0.00008715881,0.00005512156,0.0001771893,0.0002627816,0.6740253,0.00517795,0.2560583,0.06372409,0.00004394691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004038431,0.0001772197,0.9866633,0.0001639397,0.00006953141,0.00008812465,0.00004358212,0.001571839,0.007183853],"genre_scores_gemma":[0.2110226,0.0003620493,0.7754056,0.0001346834,0.00006830958,0.0003504273,0.0002121445,0.0003059651,0.01213822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008350671,"threshold_uncertainty_score":0.02201259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04155741917570525,"score_gpt":0.3755777484041451,"score_spread":0.3340203292284398,"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."}}