{"id":"W1539076612","doi":"10.1109/icsmc.2005.1571234","title":"Dealing with High Workload in Future Naval Command and Control Systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Military Strategy and Technology","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Workload; Computer science; Task (project management); Command and control; Scheduling (production processes); Architecture; Operator (biology); Task analysis; Control (management); Real-time computing; Distributed computing; Operating system; Artificial intelligence; Engineering; Systems engineering","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":[0.001347033,0.0004611283,0.0004354892,0.0005322166,0.001060399,0.001612534,0.0008410292,0.000593347,0.0009572483],"category_scores_gemma":[0.003611661,0.000301616,0.0001822552,0.0004329225,0.0004113747,0.001519891,0.0008064105,0.0005584632,0.0002999073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006860727,"about_ca_system_score_gemma":0.0007127954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004321012,"about_ca_topic_score_gemma":0.004166497,"domain_scores_codex":[0.9991067,0.0002249311,0.00005316801,0.0001453361,0.0003574019,0.0001124445],"domain_scores_gemma":[0.9985009,0.0006151993,0.0001977969,0.0001607731,0.0003957694,0.0001294783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006799905,0.0002628396,0.02759855,0.0003037392,0.0001057068,0.001606457,0.003096088,0.4203474,0.0871877,0.01797326,0.005440668,0.4353976],"study_design_scores_gemma":[0.00003927265,0.0002243745,0.00944484,0.00004336821,0.00004300396,0.0004356467,0.0007180998,0.9492964,0.01523009,0.01518549,0.009282047,0.00005750298],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3555423,0.0006114306,0.6364828,0.0007922126,0.0001004829,0.00008235756,0.00005412515,0.001510694,0.004823566],"genre_scores_gemma":[0.9561572,0.0001724147,0.04114607,0.0001106487,0.00007927402,0.0000445737,0.00008683653,0.00006387725,0.002139101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004321012,"threshold_uncertainty_score":0.008591712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001489444010674001,"score_gpt":0.1374329376657341,"score_spread":0.1359434936550601,"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."}}