{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006873992,0.0003583139,0.0008575137,0.0003780489,0.0006243885,0.0001955568,0.00189741,0.0002663124,7.551551e-7],"category_scores_gemma":[0.00009180059,0.0003168476,0.0002663144,0.0003255945,0.0003889113,0.0003815028,0.0009410181,0.0007911158,0.000001408133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001309977,"about_ca_system_score_gemma":0.0001873237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001561752,"about_ca_topic_score_gemma":0.0002696765,"domain_scores_codex":[0.9979478,0.00008381848,0.001097738,0.0002383798,0.000351611,0.0002807156],"domain_scores_gemma":[0.996748,0.001140653,0.001103359,0.0005568062,0.000396349,0.00005478545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004691102,0.00001898467,0.00003779243,0.001842839,0.0001479744,4.917502e-7,0.006894552,0.6733709,0.00002935766,0.04742364,0.00001650034,0.2702123],"study_design_scores_gemma":[0.0005079296,0.0001552328,0.00006063185,0.002167731,0.00003626138,0.00003998989,0.0001207712,0.931569,0.0001099435,0.0001218828,0.06467215,0.0004385161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001059542,0.0008967805,0.9952833,0.0002241369,0.0005238975,0.0007714375,0.0000228824,0.0001085448,0.001109452],"genre_scores_gemma":[0.868626,0.00008950308,0.1309364,0.0001042539,0.00009098717,0.00003890121,0.00002235535,0.00002398563,0.00006759567],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8675665,"threshold_uncertainty_score":0.9999284,"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."}}