{"id":"W4313149227","doi":"10.1109/tim.2022.3214282","title":"An Improved Radar Echo Signal Processing Algorithm for Industrial Liquid Level Measurement","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Algorithm; Radar; Offset (computer science); Computer science; Signal processing; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008143777,0.0002145506,0.0001892907,0.000193966,0.0006555183,0.000090179,0.00009471548,0.00006653273,0.00009057402],"category_scores_gemma":[0.000001475725,0.0002375308,0.00008298911,0.0001751601,0.00001911868,0.0002218771,8.330043e-7,0.0002594042,0.000001851481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008376605,"about_ca_system_score_gemma":0.0001427475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005602941,"about_ca_topic_score_gemma":0.00007771618,"domain_scores_codex":[0.9981292,0.00009552341,0.0003912715,0.0002844026,0.0008465315,0.0002530722],"domain_scores_gemma":[0.9995047,0.00000822715,0.00007053125,0.0001262324,0.000147445,0.0001428378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002584923,0.0001544352,5.964572e-7,0.00003257894,0.00009806711,3.989711e-7,0.0003871721,0.01397831,0.1672126,0.000002477438,0.0000658057,0.8178091],"study_design_scores_gemma":[0.008878105,0.002519107,0.00001306564,0.00005842376,0.0001548842,0.00002380608,0.003952002,0.7054531,0.2657903,0.00001460068,0.012573,0.0005695837],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008959939,0.00008290567,0.9875772,0.00007797031,0.001544404,0.001232575,0.0001410821,0.0002838451,0.0001001016],"genre_scores_gemma":[0.9969088,0.000008947049,0.001398417,0.0001173123,0.000127286,0.001360864,0.00000921307,0.0000409622,0.00002817943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9879489,"threshold_uncertainty_score":0.9686223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06592895803061889,"score_gpt":0.2505098281423491,"score_spread":0.1845808701117302,"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."}}