{"id":"W3162768907","doi":"10.1109/tim.2021.3078538","title":"Drone-Based Ceramic Insulators Condition Monitoring","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"American University of Sharjah","keywords":"Quadcopter; Drone; Insulator (electricity); Engineering; Overhead (engineering); Overhead line; Ceramic; Real-time computing; Computer science; Electrical engineering; Simulation; Aerospace engineering; Materials science","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":[0.0001042234,0.0003389101,0.0003690325,0.0005636689,0.000208037,0.0003787236,0.0006363328,0.0003245519,0.003839132],"category_scores_gemma":[0.0003265799,0.0001727642,0.0001826358,0.0001731087,0.0001477263,0.0004381247,0.0005182817,0.0002049381,0.0008797575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001940171,"about_ca_system_score_gemma":0.0002322688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002587049,"about_ca_topic_score_gemma":0.004096652,"domain_scores_codex":[0.9997954,0.00001757365,0.000007315135,0.00006247281,0.00009519971,0.0000220448],"domain_scores_gemma":[0.9997359,0.00003576244,0.00004424432,0.00005323362,0.0001017664,0.00002911667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007936065,0.0003333788,0.01394769,0.0005805747,0.00006822999,0.0005965497,0.0007621605,0.01333871,0.5662112,0.0007236333,0.004694071,0.3979502],"study_design_scores_gemma":[0.0002988155,0.003201141,0.1182105,0.0001787676,0.0002283568,0.003090951,0.0008441667,0.3992699,0.4236546,0.0006805258,0.05012548,0.0002167972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.661148,0.0005869146,0.3143051,0.000111158,0.0001249134,0.000377098,0.000764198,0.007846258,0.01473625],"genre_scores_gemma":[0.9433379,0.0001961595,0.04841075,0.0000559012,0.00002081778,0.00009070217,0.0005002042,0.00007788763,0.00730963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003839132,"threshold_uncertainty_score":0.01284319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02542945123476926,"score_gpt":0.2436370852725397,"score_spread":0.2182076340377704,"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."}}