{"id":"W1924419635","doi":"10.15439/2015f298","title":"Analysis of Inductively Coupled RFID Marker Localization Methods","year":2015,"lang":"en","type":"article","venue":"Annals of Computer Science and Information Systems","topic":"RFID technology advancements","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Kultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR","keywords":"SIGNAL (programming language); Computer science; Excitation; Amplitude; Process (computing); Identification (biology); TRACE (psycholinguistics); Acoustics; Electronic engineering; Physics; Engineering; Optics","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":[0.0005885874,0.0005192735,0.0003752217,0.000733869,0.0002142296,0.0007126674,0.001233595,0.0008375404,0.002042194],"category_scores_gemma":[0.002289577,0.0002902474,0.0005826609,0.0005570482,0.0005151616,0.0008470724,0.0006061514,0.0003601051,0.0007841035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007657686,"about_ca_system_score_gemma":0.0003239265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006201176,"about_ca_topic_score_gemma":0.000349885,"domain_scores_codex":[0.9989166,0.0002208149,0.00002698766,0.0001748711,0.0006142855,0.00004638637],"domain_scores_gemma":[0.9990237,0.000409494,0.0001440299,0.00008883278,0.0003176701,0.00001641371],"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":[0.0004560978,0.0001337312,0.003914792,0.00133529,0.0002024141,0.0009420753,0.0007717701,0.3295453,0.310017,0.07487544,0.00145598,0.27635],"study_design_scores_gemma":[0.00002084861,0.0003195641,0.001622713,0.0000894866,0.00007781458,0.0009337883,0.0001258975,0.9079697,0.06887642,0.007387233,0.01251294,0.00006369753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02163091,0.0009248967,0.972484,0.00006285471,0.00002742875,0.00004952421,0.0000228998,0.0002499996,0.004547498],"genre_scores_gemma":[0.7763813,0.002204154,0.2069032,0.0001072169,0.00005570416,0.0002235748,0.0001205996,0.0001509707,0.01385326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002042194,"threshold_uncertainty_score":0.006831825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04887489363774314,"score_gpt":0.3295713610372447,"score_spread":0.2806964673995015,"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."}}