{"id":"W2061191276","doi":"10.1145/2491465.2491469","title":"Adaptive Composition of Distributed Pervasive Applications in Heterogeneous Environments","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Autonomous and Adaptive Systems","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Distributed computing; Unavailability; Latency (audio); Ubiquitous computing; Reuse; Distributed Computing Environment; Process (computing); Human–computer interaction; Operating system","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":[0.0009312286,0.0007050591,0.0006684042,0.0006722894,0.0009870845,0.001177851,0.00139792,0.0006660961,0.001112377],"category_scores_gemma":[0.003053788,0.000598786,0.0004595994,0.0007255228,0.0007684994,0.001388823,0.00259109,0.0008420745,0.0004348329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004962027,"about_ca_system_score_gemma":0.0006352476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001363637,"about_ca_topic_score_gemma":0.001742434,"domain_scores_codex":[0.9991187,0.0002350345,0.00006996784,0.0002343331,0.000233444,0.0001085791],"domain_scores_gemma":[0.9987872,0.0003570196,0.00009774532,0.0003996724,0.0002087667,0.0001496008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001012607,0.0005701824,0.007637655,0.0002163875,0.0001839561,0.00193749,0.001371523,0.4705437,0.1711159,0.0280945,0.001873663,0.3154425],"study_design_scores_gemma":[0.00005372624,0.0001394655,0.001226379,0.00001556333,0.00005870408,0.0003329885,0.0002430923,0.9544058,0.02396108,0.01503782,0.004492936,0.00003242609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1224661,0.0001884647,0.8716845,0.00008900253,0.00004004357,0.0001706579,0.00001783946,0.002096781,0.00324656],"genre_scores_gemma":[0.7107998,0.0001997556,0.2852688,0.00006716341,0.00002957249,0.0001755053,0.00009975093,0.0002549597,0.003104777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00139792,"threshold_uncertainty_score":0.004924893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207789423212016,"score_gpt":0.2234731290403726,"score_spread":0.2013952348082525,"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."}}