{"id":"W1972625929","doi":"10.1093/comjnl/bxv003","title":"Ambient and Context-Aware Services for the Future Web","year":2015,"lang":"en","type":"article","venue":"The Computer Journal","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; World Wide Web; Mobile Web; Mobile device; Context (archaeology); Mobile technology; Mobile computing; Multimedia; Context awareness; Web service; Upload; Internet privacy; Phone; Telecommunications","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001382169,0.0001672757,0.0002007827,0.00005964947,0.000565053,0.001056276,0.001372057,0.00005245326,0.000004204315],"category_scores_gemma":[0.000006758906,0.00008657667,0.0001080737,0.00015831,0.00006174637,0.0005978967,0.0004307198,0.0003211363,0.00002594973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004634969,"about_ca_system_score_gemma":0.00012491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000143247,"about_ca_topic_score_gemma":0.00008625715,"domain_scores_codex":[0.9986215,0.0002408507,0.0002739732,0.0002287486,0.0003610402,0.0002738782],"domain_scores_gemma":[0.9982529,0.0004693505,0.0002333835,0.000449129,0.0004065699,0.0001887194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004456368,0.00005479842,0.0007766672,0.00002765526,0.000172937,0.00001885993,0.007515968,0.0001004694,0.00004048004,0.002812329,0.04532597,0.9431093],"study_design_scores_gemma":[0.002299445,0.0003176441,0.003034843,0.0001095647,0.00004421342,0.003948819,0.002276455,0.4785922,0.00008618167,0.005892251,0.5030716,0.0003267564],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02632969,0.003103713,0.9288467,0.03595315,0.005146812,0.0004636567,0.000008118314,0.00009630232,0.0000519074],"genre_scores_gemma":[0.9896778,0.00008070688,0.002692408,0.004133068,0.003280303,0.00002236697,8.904667e-7,0.00001298166,0.00009942229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9633482,"threshold_uncertainty_score":0.9999807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03363289118858721,"score_gpt":0.2554537796233071,"score_spread":0.2218208884347199,"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."}}