{"id":"W2139099332","doi":"10.1007/11839569_37","title":"Ubisafe Computing: Vision and Challenges (I)","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Ubiquitous computing; Computer science; End-user computing; Variety (cybernetics); Human–computer interaction; Construct (python library); Data science; Internet privacy; Artificial intelligence; Utility computing; Cloud computing; Cloud computing security","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":[0.0008130795,0.0005940259,0.0006066351,0.001002136,0.001556558,0.005804241,0.001497871,0.001529367,0.01005923],"category_scores_gemma":[0.001604546,0.000440044,0.000319979,0.00210297,0.002151137,0.0082103,0.0025258,0.002616516,0.004011739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001327374,"about_ca_system_score_gemma":0.001229066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004492002,"about_ca_topic_score_gemma":0.005075479,"domain_scores_codex":[0.9995614,0.00008365724,0.00002085221,0.00008121711,0.0001764065,0.00007652405],"domain_scores_gemma":[0.999562,0.00009636721,0.00001508115,0.00008769943,0.0001555605,0.00008319218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009918679,0.00004630296,0.0005287962,0.000393544,0.000009900284,0.0000740657,0.0005544044,0.001667077,0.002313064,0.2062743,0.1173979,0.6706414],"study_design_scores_gemma":[0.000008026974,0.00004221489,0.0008223451,0.0004520716,0.000009058754,0.0006023145,0.0005422263,0.01608461,0.003057248,0.1735096,0.804835,0.00003529788],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02104635,0.2502123,0.4046298,0.03678298,0.008084997,0.0001813029,0.0004897902,0.004299168,0.2742733],"genre_scores_gemma":[0.3068393,0.1485077,0.3252911,0.006797255,0.003596157,0.0003496368,0.001391528,0.001183487,0.2060437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01005923,"threshold_uncertainty_score":0.03365153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0349413565202185,"score_gpt":0.2588513379474491,"score_spread":0.2239099814272306,"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."}}