{"id":"W2327815765","doi":"10.1177/1541931213571402","title":"Drivers’ Mental Workload In Agricultural Semi-Autonomous Vehicles","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Workload; Automation; Tractor; Engineering; Seeder; Control (management); Simulation; Situation awareness; Transport engineering; Aeronautics; Computer science; Automotive engineering; Operating system; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001848933,0.0001845738,0.0002240659,0.00003662482,0.0003564424,0.00009228975,0.0002372364,0.0001347135,0.0002302473],"category_scores_gemma":[0.0000189853,0.0001311763,0.000190019,0.0001064707,0.0001419443,0.0004127223,0.0001548745,0.0002903513,0.00001819307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001260037,"about_ca_system_score_gemma":0.000007353016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003957894,"about_ca_topic_score_gemma":0.00001585348,"domain_scores_codex":[0.9989486,0.00001270459,0.0004092828,0.0002601621,0.0001006955,0.0002685402],"domain_scores_gemma":[0.9993898,0.00005324124,0.0003177019,0.0000641579,0.0001091314,0.00006601359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003304548,0.0002338107,0.6328162,0.00008392367,0.0002252382,1.041724e-7,0.2872674,0.00002812322,0.03701004,0.006965353,0.03412091,0.001215838],"study_design_scores_gemma":[0.0004621274,0.00003302386,0.8675832,0.0001024857,0.00001301579,0.000003154272,0.1287984,0.0001162946,0.001525164,0.0002358502,0.0009291864,0.0001980567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902081,0.00005462396,2.980651e-7,0.0002688087,0.0003265433,0.00025357,0.0000129242,0.00004945328,0.00882571],"genre_scores_gemma":[0.9983898,0.00001726692,0.0000798165,0.0001239422,0.00008471166,0.00002067927,0.000003606963,0.00001382518,0.00126639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.234767,"threshold_uncertainty_score":0.5349213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406021709563805,"score_gpt":0.2599342023306921,"score_spread":0.2458739852350541,"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."}}