{"id":"W3183751646","doi":"10.3390/s21155028","title":"FORESAM—FOG Paradigm-Based Resource Allocation Mechanism for Vehicular Clouds","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Resource allocation; Computer science; Cloud computing; Resource management (computing); Quality of service; Intelligent transportation system; Resource (disambiguation); SAFER; Set (abstract data type); Service (business); Distributed computing; Computer network; Transport engineering; Operations research; Computer security; Engineering; Business","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":[],"consensus_categories":[],"category_scores_codex":[0.0003054689,0.0001435926,0.0001594892,0.00006284211,0.0002356166,0.0001422359,0.0003800773,0.00009156324,0.000001512536],"category_scores_gemma":[0.0001309774,0.000148502,0.0001320796,0.0003201881,0.00001974525,0.00008071687,0.00009683378,0.0001036279,0.00003236409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004964538,"about_ca_system_score_gemma":0.0001201596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008732852,"about_ca_topic_score_gemma":0.000002193781,"domain_scores_codex":[0.9986447,0.00008763272,0.0002151558,0.000437776,0.0002376489,0.0003770862],"domain_scores_gemma":[0.9989195,0.0001931902,0.00007993008,0.0005635493,0.0001515461,0.00009228048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006161041,0.0002778071,0.0002577748,0.0002404291,0.0001323629,0.0002646101,0.002906783,0.03084841,0.01434233,0.8486881,0.03241218,0.06956764],"study_design_scores_gemma":[0.0005105057,0.00006325132,0.0001501497,0.0000362215,0.00001285562,0.00001945896,0.00002725199,0.8253503,0.07424699,0.02506752,0.07426514,0.0002503452],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2597617,0.00009390801,0.7291324,0.006380997,0.003263237,0.000250882,6.404195e-7,0.0002833666,0.0008328339],"genre_scores_gemma":[0.8366917,0.000004543014,0.1549961,0.003856672,0.002828314,0.00003849164,0.0000602474,0.00005515671,0.001468824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8236206,"threshold_uncertainty_score":0.6055734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897303880096426,"score_gpt":0.2398295564481815,"score_spread":0.2208565176472173,"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."}}