{"id":"W1964114332","doi":"10.1111/j.1559-3584.2005.tb00322.x","title":"Modeling Ship Motion Effects on Human Performance for Real Time Simulation","year":2005,"lang":"en","type":"article","venue":"Naval Engineers Journal","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Science and Technology Group","keywords":"Task (project management); Motion (physics); Computer science; Embodied cognition; Virtual actor; Engineering; Simulation; Systems engineering; Virtual reality; Human–computer interaction; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004128428,0.0001274236,0.0001316042,0.000215177,0.0002552932,0.00004763896,0.00008755229,0.0001134663,0.0008984015],"category_scores_gemma":[0.00004848305,0.0001229444,0.000110799,0.00006456201,0.000006654592,0.0002489777,0.000004118087,0.0003311366,0.000503346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00018653,"about_ca_system_score_gemma":0.00001098251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001981402,"about_ca_topic_score_gemma":5.547283e-7,"domain_scores_codex":[0.9990618,0.00005891535,0.0003222137,0.0001397215,0.0001948848,0.0002224674],"domain_scores_gemma":[0.9994479,0.0001408785,0.00008928493,0.0001125169,0.0001128748,0.00009649902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001172754,0.00004956438,0.00002792938,0.00001203637,0.00003476159,0.000001286045,0.0009646601,0.9641979,0.0008727837,0.0007928235,0.0008131334,0.03211579],"study_design_scores_gemma":[0.001310587,0.0002369134,0.001824639,0.00004389835,0.00001828802,0.00002844146,0.00003643503,0.9941555,0.0002518329,0.00004723395,0.001917745,0.0001284598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8653009,0.00001324147,0.1237164,0.0002371546,0.001007372,0.0002100636,0.000002585625,0.0001499203,0.00936238],"genre_scores_gemma":[0.9953045,0.000003788576,0.0006684353,0.0001335862,0.001416855,0.00001426011,0.00001801817,0.00002670878,0.002413856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1300036,"threshold_uncertainty_score":0.9836867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03662636272108639,"score_gpt":0.3713662451500355,"score_spread":0.3347398824289491,"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."}}