{"id":"W3013752062","doi":"10.5383/juspn.06.01.001","title":"Personal Mobile Grids: Ubiquitous Grid Environments For Personal Users","year":2015,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Plan for Science, Technology and Innovation","keywords":"Computer science; Distributed computing; Grid; Grid computing; Scheduling (production processes); Heuristic; Benchmark (surveying); Mobile device; Engineering; Operating system; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001775215,0.0003887631,0.0008444688,0.0002212511,0.0002638937,0.0005115878,0.0006200048,0.0002686595,0.000008955778],"category_scores_gemma":[0.0000902574,0.000333381,0.0003630776,0.0002138942,0.0001080056,0.00112786,0.0001875994,0.0004637569,0.00001116849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003067417,"about_ca_system_score_gemma":0.0002980797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001017913,"about_ca_topic_score_gemma":0.00002654347,"domain_scores_codex":[0.9967034,0.0003404151,0.0009628302,0.0004960233,0.0008937012,0.0006036578],"domain_scores_gemma":[0.9969026,0.0005573627,0.001072353,0.0002543619,0.0005578232,0.0006554267],"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":[0.002718993,0.002547273,0.03707226,0.001596338,0.004651022,0.001985855,0.1187512,0.02348962,0.004901881,0.0008214981,0.4041758,0.3972882],"study_design_scores_gemma":[0.01044803,0.007851636,0.002169477,0.001798352,0.0003455042,0.01487178,0.0201717,0.5260914,0.0002425442,0.0001897777,0.4138489,0.001970863],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3810472,0.02610444,0.5730257,0.0006230246,0.01671956,0.00199873,0.0001022208,0.00009395861,0.0002852372],"genre_scores_gemma":[0.9927003,0.0003841004,0.0005286215,0.0002481343,0.00548427,0.0001141491,0.000007619928,0.00004100448,0.0004917669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6116532,"threshold_uncertainty_score":0.9999118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03574278460480261,"score_gpt":0.2573400873204829,"score_spread":0.2215973027156802,"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."}}