{"id":"W2789483321","doi":"10.5539/mas.v12n4p30","title":"A Power Saving Hybrid Technique for IoT","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Microcontroller; Installation; Computer science; Battery (electricity); Embedded system; Software; Internet of Things; Sleep mode; Power (physics); Mode (computer interface); Computer hardware; Real-time computing; Power consumption; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001309798,0.0001604241,0.0001492023,0.0002028169,0.0008995038,0.0003807296,0.002207853,0.00003743703,0.000002476605],"category_scores_gemma":[0.00005510269,0.0001496306,0.00004827756,0.000727054,0.0004880906,0.0002725795,0.0007520793,0.0001153573,0.00006672869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009194408,"about_ca_system_score_gemma":0.0002969404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003554323,"about_ca_topic_score_gemma":5.019903e-7,"domain_scores_codex":[0.9978217,0.000008463524,0.0002069864,0.0008007411,0.0004381356,0.0007239059],"domain_scores_gemma":[0.9987843,0.00006813533,0.00008699571,0.0007338329,0.0001830395,0.0001436735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000626183,0.0000304538,0.00001991842,0.000007008393,0.000002066476,0.000001857285,0.001192247,0.00001042331,0.9353449,0.02461175,0.001768747,0.03700439],"study_design_scores_gemma":[0.0002320064,0.0001205892,0.0002718097,0.00002380585,0.000002145186,0.00003161911,0.000008790681,0.4355748,0.4455119,0.1087105,0.009099619,0.0004123667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009311978,0.00001066765,0.9644413,0.0002041376,0.002146672,0.0004703561,2.328466e-7,0.0002813226,0.02313334],"genre_scores_gemma":[0.7574592,1.334438e-7,0.241483,0.0004033186,0.0005018979,0.00006172329,1.786816e-7,0.000009427753,0.00008111371],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7481472,"threshold_uncertainty_score":0.6918347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556005544400255,"score_gpt":0.2557028545856173,"score_spread":0.2401427991416147,"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."}}