{"id":"W4388441585","doi":"10.18280/isi.280520","title":"Enhancing Lifespan and Energy Efficiency in Mobile Smart Dust Networks","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Green IT and Sustainability","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Computer science; Astrobiology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004352464,0.00024159,0.0002799995,0.0003332734,0.0002847855,0.0003481992,0.0004512631,0.0003020182,0.0006460819],"category_scores_gemma":[0.001466054,0.00009977188,0.0001297935,0.0002044258,0.0002358341,0.0009629647,0.0005710824,0.000149945,0.000148405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003876551,"about_ca_system_score_gemma":0.0002258849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004983477,"about_ca_topic_score_gemma":0.0009176789,"domain_scores_codex":[0.9998549,0.00004412788,0.00000660161,0.00003131189,0.00003123149,0.00003185428],"domain_scores_gemma":[0.9995099,0.0002282472,0.00006706795,0.00006728654,0.00008835755,0.00003899687],"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":[0.0003843456,0.0002068875,0.01038247,0.0003679206,0.00005944283,0.0004079664,0.0004359779,0.6263703,0.1115624,0.024885,0.002349808,0.2225875],"study_design_scores_gemma":[0.00002737706,0.0004156481,0.004391273,0.00004169783,0.00004119192,0.0003884896,0.0002902657,0.9511529,0.02314083,0.0126596,0.007428199,0.00002259718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6289487,0.00220859,0.3576846,0.0004255188,0.00009099958,0.0000624777,0.0001218097,0.000519404,0.009937743],"genre_scores_gemma":[0.9878041,0.0002827919,0.01109526,0.00002522694,0.00001064858,0.00001658031,0.00002918423,0.0000123317,0.0007239644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006460819,"threshold_uncertainty_score":0.002812624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005530874159638867,"score_gpt":0.1969545693466421,"score_spread":0.1914236951870032,"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."}}