{"id":"W2395625402","doi":"","title":"A Theoretical and Empirical Approach in Assessing Motivational Factors: From Serious Games To an ITS","year":2011,"lang":"en","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Empirical research; Skin conductance; Serious game; Cognitive psychology; Factor (programming language); Artificial intelligence; Psychology; Machine learning; Multimedia; Engineering; Mathematics; Statistics","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":[0.006462467,0.0009423475,0.0003952069,0.002231585,0.0005572323,0.002511563,0.001012313,0.0007743938,0.001981124],"category_scores_gemma":[0.03565492,0.0003755981,0.0005048474,0.00102334,0.00261038,0.002211341,0.001570617,0.001344905,0.0002067989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474858,"about_ca_system_score_gemma":0.001125477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411228,"about_ca_topic_score_gemma":0.00182698,"domain_scores_codex":[0.9955302,0.002834867,0.0002604671,0.0004276757,0.0008142767,0.0001325849],"domain_scores_gemma":[0.9810147,0.01441371,0.001361349,0.0007296471,0.001897087,0.000583396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007463004,0.004321008,0.4931106,0.002330661,0.0005005079,0.0003535883,0.01439243,0.01316439,0.01957714,0.1015837,0.001185361,0.3487344],"study_design_scores_gemma":[0.0003137237,0.01452742,0.5734055,0.001453485,0.0007043445,0.001244172,0.0314566,0.1940195,0.02537922,0.1352151,0.02202232,0.0002586117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7834877,0.0009128347,0.1889866,0.001404752,0.00007537047,0.001476664,0.0001652437,0.0001125486,0.02337826],"genre_scores_gemma":[0.9592547,0.0004081136,0.03880195,0.0001921168,0.00001945425,0.0006542518,0.00008453307,0.000009114729,0.0005757844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006462467,"threshold_uncertainty_score":0.03417724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07621308954476433,"score_gpt":0.304655268077322,"score_spread":0.2284421785325576,"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."}}