{"id":"W2339569547","doi":"10.1177/2327857915041001","title":"Improving the Ergonomics of Cognitive Assessment with Serious Games","year":2015,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Usability; Cognition; Cognitive ergonomics; Human factors and ergonomics; USable; Health care; Population; Computer science; Heuristic evaluation; Human–computer interaction; Applied psychology; Poison control; Psychology; Medicine; Multimedia; Medical emergency","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":[0.002406115,0.001643952,0.0006952368,0.001159756,0.0002939894,0.001845194,0.001141202,0.0006173645,0.002754288],"category_scores_gemma":[0.01140206,0.000436482,0.0008353852,0.0003417615,0.0003975176,0.001407435,0.001812921,0.0006168372,0.000561035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003554927,"about_ca_system_score_gemma":0.0007961277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00150874,"about_ca_topic_score_gemma":0.002762433,"domain_scores_codex":[0.9983754,0.0007200755,0.0002011809,0.0001685458,0.0003805377,0.0001542858],"domain_scores_gemma":[0.994079,0.003830716,0.0003770117,0.0003675765,0.0008918997,0.0004538852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003403683,0.009232198,0.0564124,0.003167648,0.0003859033,0.000766521,0.00553067,0.01171646,0.1173386,0.0025244,0.006907459,0.782614],"study_design_scores_gemma":[0.00353914,0.05872718,0.5042154,0.00278221,0.00182074,0.006260511,0.006843869,0.195126,0.1231833,0.01799853,0.07828616,0.001217092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.781491,0.0008968732,0.2027271,0.0006974285,0.0001932788,0.002020497,0.0002885159,0.002996765,0.008688451],"genre_scores_gemma":[0.7133421,0.0009546559,0.2810129,0.0003323273,0.00006995834,0.0009931035,0.0003137454,0.0001011694,0.002879971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002754288,"threshold_uncertainty_score":0.01272494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02814868418194789,"score_gpt":0.3350679626594676,"score_spread":0.3069192784775198,"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."}}