{"id":"W1979002183","doi":"10.1109/isccsp.2010.5463384","title":"Invited paper: Self-adaptive middleware for the design of context-aware software applications in public transit systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Public transport; Middleware (distributed applications); Computer science; Context (archaeology); Transit (satellite); Software; Context awareness; Ubiquitous computing; Mobile computing; Adaptation (eye); Open source software; Human–computer interaction; World Wide Web; Transport engineering; Telecommunications; Engineering; Distributed computing; Operating system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002188985,0.0005705775,0.0003833248,0.0004086054,0.0007238604,0.002448351,0.00163718,0.002143392,0.008800321],"category_scores_gemma":[0.004567245,0.0003578508,0.0004728589,0.0004927128,0.0006928721,0.003135183,0.001131785,0.001411211,0.001915722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006083249,"about_ca_system_score_gemma":0.0007881419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00183076,"about_ca_topic_score_gemma":0.001530168,"domain_scores_codex":[0.9989767,0.0003339434,0.00007324689,0.0002310464,0.0002827715,0.0001023277],"domain_scores_gemma":[0.9987499,0.0004457601,0.00004054972,0.0001168287,0.0004377291,0.0002091431],"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":[0.0007530923,0.000384375,0.004646028,0.001583531,0.0001662961,0.00234799,0.007189595,0.04236317,0.07606981,0.1276032,0.2179959,0.5188969],"study_design_scores_gemma":[0.000164349,0.0006187402,0.001710255,0.0002628404,0.0001777884,0.001398616,0.001472378,0.1666583,0.03549771,0.03651885,0.7553883,0.0001317995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02450976,0.004325076,0.9346425,0.009610867,0.006151184,0.0003485059,0.00010331,0.002733325,0.01757555],"genre_scores_gemma":[0.3788576,0.00743556,0.4871619,0.003757182,0.004776727,0.0006544378,0.0006022373,0.002064544,0.1146899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008800321,"threshold_uncertainty_score":0.02944005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05349638021716089,"score_gpt":0.2454434788418909,"score_spread":0.19194709862473,"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."}}