{"id":"W4401821692","doi":"10.18280/i2m.230406","title":"Optimizing Energy Efficiency in Wireless Sensor Networks Using Dijkstra's Algorithm","year":2024,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dijkstra's algorithm; Wireless sensor network; Computer science; Energy (signal processing); Algorithm; Real-time computing; Computer network; Mathematics; Theoretical computer science; Shortest path problem; Statistics; Graph","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006752557,0.0003763656,0.0003531776,0.0005196593,0.0001814752,0.0005538706,0.0008294118,0.0002793769,0.00001241613],"category_scores_gemma":[0.00001967196,0.000367735,0.0001414151,0.001766306,0.0001184883,0.0007637004,0.0002485565,0.0004519593,0.00001145915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003277889,"about_ca_system_score_gemma":0.0001451616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001719027,"about_ca_topic_score_gemma":0.00003541496,"domain_scores_codex":[0.9966539,0.0003537438,0.0006557383,0.0009737491,0.0005156734,0.0008472461],"domain_scores_gemma":[0.9987947,0.0003349839,0.0001408943,0.0005288641,0.00007178302,0.0001287138],"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":[0.000007368684,0.00006103815,0.0002888986,0.00001156276,0.00002700662,0.0002417869,0.0002502691,0.8364887,0.001141919,0.01117925,0.00005450518,0.1502477],"study_design_scores_gemma":[0.0004379759,0.00007748981,0.0002837462,0.000109705,0.00001473268,0.00006672674,0.00006356038,0.99633,0.00177443,0.0001821902,0.0002886655,0.0003707418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1071271,0.0007708207,0.8884283,0.0004839989,0.002126245,0.0001459519,0.000003544674,0.0006553112,0.0002587536],"genre_scores_gemma":[0.8529427,0.0001654122,0.1461665,0.0003742713,0.0002199451,0.00002405947,0.00002579971,0.00003621731,0.0000450511],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7458156,"threshold_uncertainty_score":0.9998775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986283488700261,"score_gpt":0.2711961416605358,"score_spread":0.2513333067735332,"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."}}