{"id":"W4292826035","doi":"10.1109/jiot.2022.3201177","title":"RPL Point-to-Point Communication Paths: Analysis and Enhancement","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Overhead (engineering); Computer network; Routing protocol; Multiprotocol Label Switching; Shortest path problem; Routing (electronic design automation); Point-to-point; Path (computing); Network topology; Topology (electrical circuits); Lossy compression; Distributed computing; Quality of service; Mathematics; Graph; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002384228,0.001097997,0.0006123462,0.001871537,0.0006535847,0.001321102,0.001643334,0.000959782,0.002105327],"category_scores_gemma":[0.01020423,0.0004614127,0.0007378901,0.001680917,0.0007918771,0.003277947,0.001431548,0.001512038,0.0008168591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604959,"about_ca_system_score_gemma":0.001562485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002455434,"about_ca_topic_score_gemma":0.002210398,"domain_scores_codex":[0.9970817,0.0004711809,0.0001173174,0.0002612646,0.001803587,0.000264966],"domain_scores_gemma":[0.993769,0.001967147,0.0007525131,0.001068343,0.002291235,0.0001517185],"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":[0.000332296,0.0001974801,0.004469958,0.0006256342,0.0001006865,0.0005027291,0.0003103543,0.5137067,0.02406705,0.05163805,0.01321268,0.3908364],"study_design_scores_gemma":[0.00001283409,0.0001249292,0.0006323636,0.00002475414,0.00002490258,0.0003732559,0.0000464673,0.9787065,0.006493185,0.0061271,0.007404669,0.00002898101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02188781,0.001253001,0.9678028,0.0005977054,0.0001352803,0.0002219222,0.0002160655,0.002197915,0.005687481],"genre_scores_gemma":[0.4896222,0.002049266,0.5018255,0.0002796678,0.0001915267,0.0003872082,0.0006588288,0.0004966631,0.00448913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002455434,"threshold_uncertainty_score":0.01260918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009260761465455365,"score_gpt":0.2341378124544521,"score_spread":0.2248770509889967,"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."}}