{"id":"W4318422669","doi":"10.46855/energy-proceedings-9930","title":"Optimal Configuration of Dynamic Wireless Charging Infrastructure for Ehighway Applications","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada","keywords":"Wireless; Computer science; Telecommunications; 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":[0.0002966823,0.0006279114,0.0006932684,0.0003778137,0.0004599362,0.001254491,0.0009134358,0.0007224552,0.004936142],"category_scores_gemma":[0.001128861,0.0003943705,0.000256519,0.0005951914,0.0004130839,0.001108105,0.0008425644,0.0005612679,0.0006545026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000842475,"about_ca_system_score_gemma":0.0006837086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447434,"about_ca_topic_score_gemma":0.002170665,"domain_scores_codex":[0.9997299,0.00006714723,0.000007299207,0.0000559793,0.00003447337,0.0001052487],"domain_scores_gemma":[0.9997943,0.00006651977,0.00002191803,0.00003583278,0.00004436864,0.00003714297],"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":[0.0004147042,0.0001132019,0.001193943,0.0001079192,0.00003702159,0.0001713006,0.00006620192,0.8996254,0.01642295,0.01426057,0.004142841,0.06344401],"study_design_scores_gemma":[0.00002074061,0.00005488882,0.0005556977,0.00000822021,0.0000125232,0.00006071289,0.00008420191,0.9863337,0.002652116,0.009192429,0.001013803,0.00001107284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2077671,0.0007820835,0.7598653,0.0009458916,0.000183406,0.0001382384,0.000425594,0.000895424,0.0289971],"genre_scores_gemma":[0.9841816,0.00008803889,0.01370544,0.00002970215,0.00001220238,0.00002477735,0.00006628131,0.00003589378,0.001856066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004936142,"threshold_uncertainty_score":0.01651299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007438611507688546,"score_gpt":0.2337339203032786,"score_spread":0.2262953087955901,"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."}}