{"id":"W2966822194","doi":"10.25147/ijcsr.2017.001.1.32","title":"Semi-network OS and Embedded OS for Co-mobile Computing","year":2019,"lang":"en","type":"article","venue":"International Journal of Computing Sciences Research","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Mobile device; Mobile computing; Embedded system; Network architecture; Computer network; Architecture; Mobile database; Mobile technology; Distributed computing; Operating system; Mobile station; Base station","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01024801,0.0001613904,0.0003413112,0.0004919744,0.0004993774,0.001285945,0.003454518,0.00007410749,0.00001403458],"category_scores_gemma":[0.0003234716,0.0001358913,0.000141272,0.0007570511,0.0002720817,0.0005098663,0.0006843988,0.0004761192,0.00002998666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001135282,"about_ca_system_score_gemma":0.0004358945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001417891,"about_ca_topic_score_gemma":9.562467e-7,"domain_scores_codex":[0.9956099,0.0003793109,0.0007686546,0.000466587,0.002092814,0.0006827509],"domain_scores_gemma":[0.994621,0.002653775,0.0005328857,0.0002392985,0.001774352,0.0001787318],"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":[0.0001790313,0.0003645494,0.06163375,0.000186858,0.0004411329,0.0001412991,0.008309209,0.692125,0.00340063,0.07860187,0.03947002,0.1151467],"study_design_scores_gemma":[0.00122656,0.0009619808,0.002637185,0.0006024913,0.000003564689,0.0005461466,0.000453297,0.968804,0.0003721896,0.004288481,0.0198489,0.0002551778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5270333,0.0003760005,0.4656763,0.000580007,0.002898139,0.0003954086,0.000004476685,0.00004378544,0.002992629],"genre_scores_gemma":[0.966939,0.00001298141,0.03158094,0.0001181947,0.001172744,0.000001649094,0.000002338741,0.000008659964,0.0001635076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4399057,"threshold_uncertainty_score":0.9997508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06029914176261003,"score_gpt":0.4361068322828783,"score_spread":0.3758076905202683,"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."}}