{"id":"W4400877791","doi":"10.1007/978-3-031-64776-5_33","title":"Providing an Intelligent Hybrid Routing Method in Wireless Sensor Networks","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Computer network; Wireless sensor network; Routing (electronic design automation); Hybrid routing; Dynamic Source Routing; Routing protocol","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":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002027909,0.001115425,0.001533832,0.0006626953,0.0001792113,0.001127194,0.001145042,0.00122525,0.000005009708],"category_scores_gemma":[0.00003959633,0.001016772,0.0002261916,0.0004792632,0.0001068566,0.0002591912,0.0006666995,0.002874444,0.000005838776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000411409,"about_ca_system_score_gemma":0.00007601485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002921773,"about_ca_topic_score_gemma":0.0005954523,"domain_scores_codex":[0.9940814,0.0003907485,0.001512936,0.002161521,0.0005950132,0.001258367],"domain_scores_gemma":[0.9963832,0.001444275,0.0005251654,0.001246534,0.0001147393,0.0002860604],"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":[0.00001512974,0.00002044526,0.00009652606,0.000143143,0.00005541786,0.0005896309,0.0003156341,0.8616708,0.000005621668,0.09336835,0.00002368519,0.04369561],"study_design_scores_gemma":[0.0002147444,0.0001042732,0.000005431873,0.003953356,0.00003726887,0.0002387599,0.0000118906,0.9901311,0.00001694338,0.001969049,0.00226605,0.00105118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003536005,0.01836762,0.9699726,0.0001191022,0.004321849,0.0009613821,0.000004600618,0.0003735189,0.005525719],"genre_scores_gemma":[0.9828219,0.001559719,0.008454793,0.0002569997,0.003007951,0.00007138464,0.00005727376,0.0002872662,0.003482668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9824684,"threshold_uncertainty_score":0.9999098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01908011344110345,"score_gpt":0.253846288669286,"score_spread":0.2347661752281826,"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."}}