{"id":"W2982909732","doi":"10.1109/tie.2019.2949520","title":"Multiresonant Chipless RFID Array System for Coating Defect Detection and Corrosion Prediction","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"RFID technology advancements","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Chipless RFID; Pipeline (software); Coating; Antenna (radio); Acoustics; Materials science; Wireless; Radio-frequency identification; Electronic engineering; Resonator; Computer science; Engineering; Electrical engineering; Optoelectronics; Composite material; Physics; Telecommunications; Mechanical 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":[0.0002619422,0.0004996751,0.0004580925,0.0003834356,0.0001328613,0.0003389911,0.001059553,0.0007215703,0.001446952],"category_scores_gemma":[0.0004692005,0.000240804,0.0002452535,0.0002224405,0.0001606634,0.000567317,0.0003650138,0.0003034388,0.001284852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002001275,"about_ca_system_score_gemma":0.0001657052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001816384,"about_ca_topic_score_gemma":0.0003166844,"domain_scores_codex":[0.9995635,0.0000679249,0.00002048317,0.0001566551,0.0001604219,0.00003096621],"domain_scores_gemma":[0.9995919,0.00008070666,0.0001009924,0.0000824802,0.0001247855,0.0000191426],"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":[0.0004224417,0.0001068628,0.003024275,0.0002572819,0.00004091387,0.0002783093,0.0001084802,0.003606207,0.8387292,0.0008890402,0.002183439,0.1503536],"study_design_scores_gemma":[0.0001010864,0.002169103,0.009184963,0.00004615299,0.0001557916,0.003135581,0.00008892676,0.2012451,0.7661378,0.00075068,0.0168651,0.0001197963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1805768,0.001238673,0.8079083,0.0002731215,0.0003308636,0.0001033596,0.0002494682,0.005025193,0.004294213],"genre_scores_gemma":[0.8303894,0.0003220966,0.1619008,0.0003310965,0.00008901685,0.00006943325,0.0001885139,0.00006067302,0.006648952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001446952,"threshold_uncertainty_score":0.004840553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326100990487373,"score_gpt":0.2102590068190934,"score_spread":0.1969979969142197,"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."}}