{"id":"W2549372462","doi":"10.1109/jsen.2016.2631618","title":"Robust Ultra-High Resolution Microwave Planar Sensor Using Fuzzy Neural Network Approach","year":2016,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates - Technology Futures","keywords":"Artificial neural network; Computer science; Fuzzy logic; Microwave; Fault (geology); Planar; Artificial intelligence; Electronic engineering; Real-time computing; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003006803,0.0003438917,0.000350688,0.0002098001,0.0002543691,0.00008404541,0.0002961233,0.0003218212,0.0000170766],"category_scores_gemma":[0.00009433069,0.0002549058,0.0001436752,0.0002791664,0.0001608497,0.000222076,0.00001556824,0.0006848698,0.00003238801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003874167,"about_ca_system_score_gemma":0.00002737107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007094923,"about_ca_topic_score_gemma":0.000001882718,"domain_scores_codex":[0.997918,0.00009128233,0.000476765,0.0002698704,0.0003573833,0.0008867778],"domain_scores_gemma":[0.9991242,0.0001348615,0.0001438543,0.0003241792,0.00009508398,0.0001777727],"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":[0.0000241834,0.00001154642,0.0001694199,0.00001854911,0.00007711166,0.0001447072,0.00003604492,0.7482828,0.2413932,0.00005272829,0.007708951,0.00208077],"study_design_scores_gemma":[0.003865956,0.0002614511,0.002282084,0.0007821877,0.0003895917,0.02691573,0.001153057,0.8337833,0.1201634,0.003944166,0.003714562,0.002744508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8031542,0.0006171521,0.1924777,0.000150503,0.00171392,0.0001578012,0.00002607863,0.0006543207,0.001048357],"genre_scores_gemma":[0.9408138,0.0002631345,0.05711335,0.00002527376,0.001549602,0.000001898917,0.000001653632,0.00009594191,0.00013528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1376597,"threshold_uncertainty_score":0.9999903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03070384966704472,"score_gpt":0.2130980500789605,"score_spread":0.1823942004119158,"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."}}