{"id":"W109494006","doi":"10.1007/978-3-642-33687-4_21","title":"Developing Serious Games Specifically Adapted to People Suffering from Alzheimer","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Serious game; Set (abstract data type); Perception; Computer science; Cognition; Psychology; Multimedia; Psychiatry; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007727158,0.0004899981,0.0006063127,0.000676299,0.000567572,0.0003433962,0.002308413,0.000669133,0.0001916611],"category_scores_gemma":[0.0003033972,0.0004986988,0.00009871773,0.0007798165,0.0009360498,0.0003662221,0.0009504873,0.0008397035,0.000245375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005612649,"about_ca_system_score_gemma":0.0008454114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001319546,"about_ca_topic_score_gemma":0.02006156,"domain_scores_codex":[0.9960358,0.00005359361,0.0004729489,0.001257975,0.0010739,0.001105844],"domain_scores_gemma":[0.9978908,0.0005373223,0.0002006977,0.000807477,0.0002418988,0.0003218631],"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":[0.00001352486,0.00002038634,0.00108608,0.000008317665,0.00004584038,0.00004384522,0.01961228,0.0006145749,0.0002213042,0.02310405,0.00006482036,0.955165],"study_design_scores_gemma":[0.001600216,0.0004433942,0.05178884,0.003829644,0.0002806079,0.00006995309,0.0001085412,0.005035981,0.01054348,0.3764886,0.5410718,0.008738917],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007969417,0.001737163,0.9742409,0.006793121,0.003572646,0.0008946762,0.00001661699,0.000615325,0.004160111],"genre_scores_gemma":[0.6910681,0.0001487765,0.3053705,0.001634772,0.001491074,0.0000187967,0.000008410642,0.00006884594,0.0001907402],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.946426,"threshold_uncertainty_score":0.9997464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03623503828401428,"score_gpt":0.2805746285321281,"score_spread":0.2443395902481138,"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."}}