{"id":"W3020902453","doi":"10.1007/978-3-319-14227-2_31","title":"A Comprehensive View of Ubiquitous Learning Context Usage in Context-Aware Learning System","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Context (archaeology); Computer science; Set (abstract data type); Order (exchange); Data science; Human–computer interaction; Artificial intelligence; Knowledge management; Geography","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":[0.0003722977,0.0007438372,0.0008443744,0.001753793,0.000713216,0.003995324,0.001088211,0.001434735,0.002435283],"category_scores_gemma":[0.0006466136,0.0005747383,0.0007050819,0.002794636,0.001035032,0.005882611,0.001389715,0.001761034,0.0009510652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008715176,"about_ca_system_score_gemma":0.0007007842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002665267,"about_ca_topic_score_gemma":0.002549781,"domain_scores_codex":[0.999548,0.00008719042,0.00004820451,0.0001126727,0.0001595254,0.00004434202],"domain_scores_gemma":[0.9997866,0.00008757962,0.00001524837,0.00003373254,0.00005605641,0.00002090151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004878674,0.0001025304,0.001498263,0.001000553,0.0001093001,0.0005216818,0.001288088,0.01857302,0.008970957,0.5982633,0.009760753,0.3598628],"study_design_scores_gemma":[0.000008605417,0.0001569543,0.004137843,0.001179405,0.0002460145,0.002919998,0.001126151,0.1568364,0.006335668,0.4306737,0.396266,0.00011328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01775448,0.1623041,0.7279683,0.002582168,0.0008020682,0.000107712,0.0004312959,0.0009062912,0.08714364],"genre_scores_gemma":[0.4821669,0.1330746,0.3392051,0.001712652,0.00155964,0.0003040591,0.00103116,0.0002322812,0.0407136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003995324,"threshold_uncertainty_score":0.008146882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02797196097909742,"score_gpt":0.2406423808952373,"score_spread":0.2126704199161399,"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."}}