{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002197978,0.0001049547,0.0001314972,0.00008677032,0.00005685743,0.000196813,0.0002563768,0.00005379588,0.00006834867],"category_scores_gemma":[0.00006024828,0.00007923994,0.00001839216,0.0001491859,0.00002643932,0.0005319847,0.0001382747,0.0001274724,0.000009919168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002550346,"about_ca_system_score_gemma":0.00002947932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001335498,"about_ca_topic_score_gemma":0.000003331507,"domain_scores_codex":[0.998993,0.0001124171,0.0001661364,0.000366511,0.0001740675,0.0001878406],"domain_scores_gemma":[0.9995676,0.00009315542,0.00002752463,0.000157441,0.00004259417,0.0001117066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00000281984,0.00007642961,0.09424023,0.000002889499,0.000004877321,0.000005123464,0.008897502,0.00005212678,0.0003756825,0.8940917,0.000007926851,0.002242751],"study_design_scores_gemma":[0.0001355358,0.0001178725,0.9064274,0.00004533201,0.00000175297,0.000006685836,0.001150826,0.0818828,0.002089049,0.007399972,0.000481592,0.0002611933],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6057459,0.000007377481,0.3897524,0.00005148487,0.00006619994,0.0000614155,3.912396e-7,0.00004849112,0.004266422],"genre_scores_gemma":[0.9348246,2.600702e-7,0.06477799,0.0001506666,0.00005505416,0.00000520982,0.000001469102,0.000005896378,0.0001788842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8866917,"threshold_uncertainty_score":0.3231311,"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."}}