{"id":"W4230176027","doi":"10.1109/mprv.2015.21","title":"UbiComp 2014","year":2015,"lang":"en","type":"article","venue":"IEEE Pervasive Computing","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Ubiquitous computing; Context-aware pervasive systems; Computer science; Wearable computer; Variety (cybernetics); Human–computer interaction; Smart environment; Wearable technology; World Wide Web; Ubiquitous robot; Internet of Things; Embedded system; Artificial intelligence","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008397129,0.0002829558,0.0003266099,0.0001715176,0.0003207613,0.0003619067,0.001515613,0.00009509179,0.000002338765],"category_scores_gemma":[0.0001334283,0.0002782336,0.0001397057,0.00047713,0.00006122851,0.0004575666,0.000652606,0.0003174055,0.0009711296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315038,"about_ca_system_score_gemma":0.000215631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000663528,"about_ca_topic_score_gemma":0.000001470782,"domain_scores_codex":[0.9975647,0.0001472269,0.0004110021,0.0006630006,0.0004839193,0.0007301783],"domain_scores_gemma":[0.9980893,0.0002417823,0.0001877002,0.0007183384,0.0004015489,0.0003613244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001796877,0.0002621856,0.01546504,0.00007700841,0.0001153585,0.000360674,0.01570377,0.008662984,0.002663003,0.006686489,0.7060781,0.2439074],"study_design_scores_gemma":[0.001593709,0.0002565591,0.003948398,0.0001642018,0.00001773403,0.0003317677,0.0001860851,0.8870403,0.005707739,0.005703507,0.09385426,0.001195773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1831724,0.0003908392,0.7768084,0.0009380011,0.02754921,0.0001679014,1.688598e-7,0.0007694254,0.0102037],"genre_scores_gemma":[0.9083434,0.000004494687,0.08222465,0.001448291,0.007634494,0.000002948304,0.000003214193,0.00003596327,0.0003025571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8783773,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05058841630956252,"score_gpt":0.27566538439444,"score_spread":0.2250769680848775,"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."}}