{"id":"W2405263560","doi":"","title":"Personalized presentation of multimedia objects for home healthcare environments: a peer-based intelligent tutoring approach.","year":2012,"lang":"en","type":"article","venue":"International Conference on User Modeling, Adaptation, and Personalization","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Presentation (obstetrics); Multimedia; Curriculum; Value (mathematics); Health care; Intelligent tutoring system; Personalized learning; Human–computer interaction; Order (exchange); World Wide Web; Teaching method; Open learning; Cooperative learning; Machine learning; Mathematics education; Psychology","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":[0.0005553552,0.0002170734,0.0002122133,0.0002428612,0.0001713885,0.0001314504,0.0002979502,0.00009716961,0.0000241632],"category_scores_gemma":[0.0001332077,0.000217845,0.00009239285,0.0001175756,0.00004172478,0.0007240991,0.00003661914,0.0001154628,0.000004611393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001381991,"about_ca_system_score_gemma":0.0001134653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002267507,"about_ca_topic_score_gemma":0.00001037765,"domain_scores_codex":[0.9979908,0.0001170104,0.0004491648,0.0004016173,0.0007729081,0.000268451],"domain_scores_gemma":[0.9986197,0.0001097154,0.0003106237,0.0001701644,0.0006637581,0.0001259928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001432482,0.0002732257,0.004503653,0.00018835,0.00009541804,3.618984e-7,0.04018022,0.1101569,0.001048638,0.8382536,0.00002829054,0.005128132],"study_design_scores_gemma":[0.0006115842,0.0001108852,0.0003671061,0.0001353223,0.0000143464,0.00000233109,0.00297679,0.9916538,0.0005148094,0.0005538795,0.00283745,0.0002217101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009205814,0.0002467842,0.9886482,0.0003380753,0.0007120006,0.0004654342,0.00002698462,0.00005191024,0.0003048244],"genre_scores_gemma":[0.9527305,0.00008480605,0.04403222,0.0001298546,0.0002628757,0.0001203413,0.000259709,0.00002170407,0.002357966],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.944616,"threshold_uncertainty_score":0.8883462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1333079331296142,"score_gpt":0.318181196506369,"score_spread":0.1848732633767548,"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."}}