{"id":"W3007388547","doi":"10.1002/itl2.153","title":"Dynamic wireless charging for CAEV taxi fleet in urban environment","year":2020,"lang":"en","type":"article","venue":"Internet Technology Letters","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Government of Ontario; Ministry of Energy","keywords":"Software deployment; Transport engineering; Wireless; Computer science; Fuel efficiency; Range (aeronautics); Vehicle-to-vehicle; Key (lock); Automotive engineering; Computer security; Telecommunications; Engineering; Computer network","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":[0.0001327217,0.0003391765,0.0003246128,0.0001860669,0.00049252,0.0005182493,0.0007529764,0.0003638566,0.001764889],"category_scores_gemma":[0.0002273564,0.0001222896,0.0002393009,0.0003550519,0.0002083057,0.0005219824,0.0004710264,0.0003041435,0.000297752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004805143,"about_ca_system_score_gemma":0.0003721185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003532766,"about_ca_topic_score_gemma":0.004845964,"domain_scores_codex":[0.9998627,0.00002317298,0.000005797252,0.00002862843,0.00002743843,0.00005227149],"domain_scores_gemma":[0.9999375,0.00001194428,0.000008165403,0.00001056126,0.00001915234,0.00001257795],"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":[0.0002497861,0.00008883094,0.004227253,0.0001166706,0.00003874295,0.0007521235,0.0001467757,0.8174264,0.03036593,0.01217116,0.005539523,0.1288768],"study_design_scores_gemma":[0.000008049682,0.00008048749,0.0009014473,0.00000338614,0.000009741899,0.0001497149,0.0001475513,0.9899595,0.00300124,0.002819645,0.002909586,0.000009701458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3216838,0.0005042281,0.6476212,0.0006651052,0.0001645224,0.0001410181,0.0001667546,0.0007162324,0.02833727],"genre_scores_gemma":[0.9896589,0.00007651254,0.007562933,0.00002619385,0.000007336078,0.00001729192,0.00003861783,0.0000118546,0.00260034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003532766,"threshold_uncertainty_score":0.007024407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006312287046195986,"score_gpt":0.1825295908814794,"score_spread":0.1762173038352834,"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."}}