{"id":"W4405280758","doi":"10.1088/978-0-7503-6049-4ch8","title":"Hybrid channel-based foglet-assisted smart asset reporting","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Asset (computer security); Asset management; Wireless; Focus (optics); Intelligent transportation system; Visible light communication; Channel (broadcasting); Telecommunications; Communications system; Emergency management; Computer science; Computer security; Business; Engineering; Transport engineering; Finance; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001179127,0.0002241873,0.0003006725,0.000205062,0.0001914417,0.0005360704,0.0009255934,0.0004759215,0.001817234],"category_scores_gemma":[0.0001202209,0.0001228225,0.000297453,0.0002489376,0.0001316767,0.0005771146,0.0003992369,0.0003185761,0.0007432098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002275665,"about_ca_system_score_gemma":0.0002374851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001177783,"about_ca_topic_score_gemma":0.001530573,"domain_scores_codex":[0.9999228,0.000008294192,0.000002126712,0.00001899784,0.0000281076,0.00001969516],"domain_scores_gemma":[0.9999285,0.00002196115,0.000004725334,0.00001230108,0.00002376275,0.000008740677],"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":[0.0005842124,0.0006190749,0.002162715,0.0003222896,0.0001226316,0.001249607,0.0002898672,0.1847461,0.18649,0.02578951,0.04015147,0.5574725],"study_design_scores_gemma":[0.00002993582,0.0002057136,0.001118603,0.00002063973,0.00003384568,0.0006299682,0.00005337287,0.9376618,0.03277944,0.004346101,0.02308167,0.00003898376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1686882,0.002069482,0.7663445,0.0004055748,0.0007546601,0.0001606789,0.0004558234,0.00453805,0.05658305],"genre_scores_gemma":[0.8168768,0.00113422,0.1520831,0.0003615772,0.000108292,0.00005956323,0.0004665708,0.0001062652,0.02880373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001817234,"threshold_uncertainty_score":0.006079257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05141120087295342,"score_gpt":0.2780247847628711,"score_spread":0.2266135838899176,"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."}}