{"id":"W2738730522","doi":"10.5815/ijmecs.2017.07.01","title":"A Classification Framework for Context-aware Mobile Learning Systems","year":2017,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Context (archaeology); Field (mathematics); Mobile device; Context awareness; Architecture; Mobile computing; Layer (electronics); Multimedia; Human–computer interaction; Ubiquitous computing; Data science; Artificial intelligence; World Wide Web; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001317348,0.0001214936,0.0001927994,0.0003304543,0.0005808414,0.002682848,0.002404625,0.00005786004,0.000002185402],"category_scores_gemma":[0.0003423761,0.0001132056,0.00008120399,0.00009204287,0.0001932774,0.002714003,0.0002738256,0.0002028499,0.000005275479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001547535,"about_ca_system_score_gemma":0.0007804714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002183393,"about_ca_topic_score_gemma":0.000002511843,"domain_scores_codex":[0.9982852,0.00007102527,0.000437648,0.0003462321,0.0006873775,0.0001725322],"domain_scores_gemma":[0.9955541,0.0002804266,0.001146932,0.0003976532,0.00245865,0.0001622315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001290862,0.0001356948,0.002483138,0.00001045004,0.00002948659,0.000001731934,0.001598174,0.0001493614,0.0003159865,0.05662252,0.0001666166,0.9384739],"study_design_scores_gemma":[0.0006460401,0.000255354,0.02015514,0.0004956253,0.00001159816,0.0006181917,0.0006104268,0.9417397,0.0003060903,0.02108703,0.01379807,0.0002767458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04204557,0.0003095765,0.9478845,0.001788418,0.007607165,0.0002164547,0.000002315728,0.00002792831,0.0001180824],"genre_scores_gemma":[0.9759356,0.00003735376,0.02282118,0.0002462838,0.000810795,0.0000399577,0.000001118778,0.000006790731,0.0001009646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9415903,"threshold_uncertainty_score":0.9983525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04661118029122972,"score_gpt":0.3519244401455645,"score_spread":0.3053132598543347,"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."}}