{"id":"W2969734644","doi":"10.1007/s13437-019-00174-y","title":"Being prepared for emergencies: a virtual environment experiment on the retention and maintenance of egress skills","year":2019,"lang":"en","type":"article","venue":"WMU Journal of Maritime Affairs","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Retraining; Competence (human resources); Preparedness; Knowledge retention; Retention rate; Medical education; Psychology; Computer science; Computer security; Medicine; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001884971,0.000624456,0.0008599308,0.0002652829,0.0005259915,0.0006009507,0.0008303738,0.0009366233,0.00283477],"category_scores_gemma":[0.003159333,0.0004687979,0.0005188133,0.0001765461,0.0007456555,0.0007228002,0.001040062,0.001587361,0.0003961282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235932,"about_ca_system_score_gemma":0.0005661511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006434188,"about_ca_topic_score_gemma":0.0008951375,"domain_scores_codex":[0.9992222,0.000199364,0.0001051234,0.0001685897,0.0001216136,0.0001831232],"domain_scores_gemma":[0.996972,0.00144716,0.0003438513,0.0003653349,0.0002078656,0.0006638842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"nonrandomized_trial","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0612796,0.428005,0.02267904,0.0009145146,0.0002330948,0.00117154,0.02129642,0.005154325,0.3877778,0.0009288144,0.0007406255,0.06981923],"study_design_scores_gemma":[0.003464115,0.8674014,0.06872205,0.00006641202,0.0001530585,0.000238657,0.002581903,0.003879413,0.05046823,0.0004370763,0.002470634,0.0001171298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995617,0.000008174798,0.000129876,0.000009149126,0.000007265244,0.0001338882,0.00002571202,0.000003476881,0.0001207548],"genre_scores_gemma":[0.9944221,0.00007421104,0.002252417,0.00003826569,0.00001662978,0.0009538037,0.0001525514,0.000006315553,0.002083717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00283477,"threshold_uncertainty_score":0.009968758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01383547453777123,"score_gpt":0.2869596463412514,"score_spread":0.2731241718034801,"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."}}