{"id":"W4410074545","doi":"10.63471/ml24001","title":"Energy-Efficient Communication Protocols for Massive IoT Deployments: Green IoT","year":2024,"lang":"en","type":"article","venue":"Advances in Machine Learning IoT and Data Security","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wycliffe College","funders":"","keywords":"Internet of Things; Computer science; Computer network; Energy (signal processing); Computer security; Physics","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":[0.001019827,0.0002170683,0.0002385874,0.0001612104,0.0003542392,0.0003311878,0.00153246,0.00007319006,0.000002326737],"category_scores_gemma":[0.0001550389,0.0001980903,0.00003967404,0.0004256049,0.00007960218,0.0004294166,0.001781095,0.0004864264,0.000004927222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005494612,"about_ca_system_score_gemma":0.00005494468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002842003,"about_ca_topic_score_gemma":0.0001214978,"domain_scores_codex":[0.9980662,0.0002165695,0.0003512567,0.0007608535,0.0002303888,0.0003746878],"domain_scores_gemma":[0.9982743,0.0005146011,0.0001245437,0.0009586329,0.00005010031,0.00007778372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007570645,0.0002489691,0.007560872,0.0006599816,0.00005265483,0.00003184897,0.003595367,0.006825866,0.00008926868,0.03512306,0.001700769,0.9440356],"study_design_scores_gemma":[0.0002824677,0.00007548654,0.0001248847,0.0002042876,0.000005566121,0.00000585856,0.00001462377,0.6492779,0.00004107712,0.008733188,0.341066,0.0001685922],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01481002,0.03321603,0.9368808,0.00400828,0.002995511,0.005791655,0.00004784157,0.0009817358,0.001268191],"genre_scores_gemma":[0.8006273,0.001387043,0.189025,0.0009187029,0.002736634,0.003476252,0.001193797,0.0001442097,0.0004911182],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.943867,"threshold_uncertainty_score":0.8077887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02376309900197511,"score_gpt":0.3462803540350826,"score_spread":0.3225172550331075,"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."}}