{"id":"W3089627430","doi":"10.1109/ichms49158.2020.9209513","title":"Human-Autonomy Teaming for Critical Command and Control Functions","year":2020,"lang":"en","type":"article","venue":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Autonomy; Enabling; Automation; Conformity; Computer science; Control (management); Command and control; Knowledge management; Human–computer interaction; Process management; Engineering; Psychology; Artificial intelligence; Social psychology; Political science","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":[0.002663228,0.0003802427,0.0001956376,0.0004663526,0.001993153,0.00176,0.0005093648,0.0006886491,0.003260504],"category_scores_gemma":[0.005668717,0.0001835548,0.0003203117,0.000157136,0.002672204,0.002186298,0.00243457,0.001103657,0.0004485676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007760985,"about_ca_system_score_gemma":0.002737521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001235991,"about_ca_topic_score_gemma":0.00128053,"domain_scores_codex":[0.9979934,0.001179828,0.00006314682,0.0002074129,0.000403656,0.000152543],"domain_scores_gemma":[0.9977329,0.0009641934,0.0003010272,0.0003296349,0.0002827428,0.0003895034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001747383,0.0002414308,0.005396805,0.0002802818,0.00005466595,0.0001779783,0.01148926,0.0291802,0.01077077,0.7679769,0.004896286,0.1693608],"study_design_scores_gemma":[0.00009947596,0.0007837871,0.008726413,0.0002338001,0.00006188667,0.0005939126,0.007290419,0.1291218,0.009704169,0.7705838,0.07272422,0.00007642589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1368395,0.0005300371,0.7852216,0.003751693,0.000136889,0.0001918618,0.00001717005,0.000317901,0.07299342],"genre_scores_gemma":[0.9015454,0.0001707232,0.09523803,0.0001517583,0.00002521279,0.0000801286,0.00001325105,0.00002632825,0.002749155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003260504,"threshold_uncertainty_score":0.01408464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1309144508977815,"score_gpt":0.433347624041042,"score_spread":0.3024331731432606,"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."}}