{"id":"W2611266854","doi":"10.1049/iet-map.2016.0931","title":"Magneto‐dielectric substrate‐based microstrip antenna for RFID applications","year":2017,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Magneto; Microstrip antenna; Substrate (aquarium); Materials science; Dielectric; Microstrip; Antenna (radio); Optoelectronics; Electronic engineering; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002237981,0.0003193554,0.0003273465,0.000210478,0.0006666608,0.000401953,0.0004846862,0.0001596126,0.00003003442],"category_scores_gemma":[0.00004222634,0.0003136403,0.0002486973,0.0002513268,0.0001417496,0.000341012,0.00002312495,0.0001793202,0.000083041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007229637,"about_ca_system_score_gemma":0.00005653526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002711364,"about_ca_topic_score_gemma":0.00003431562,"domain_scores_codex":[0.998467,0.00002120675,0.0004277076,0.0004152978,0.0001509679,0.0005177858],"domain_scores_gemma":[0.998675,0.00004449064,0.0002070402,0.0006944658,0.0002644,0.0001145255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003574466,0.00006200165,0.0007006577,0.000138534,0.00006197341,0.000003597422,0.00003620969,0.00002506339,0.9938377,0.0002887848,0.0003300493,0.004479756],"study_design_scores_gemma":[0.001673907,0.0002328811,0.01040293,0.0001336195,0.0002830289,0.00002358774,0.0001282473,0.7972438,0.1817447,0.0011002,0.006034987,0.0009981471],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05860563,0.001388937,0.9369703,0.000519327,0.000185652,0.001285376,0.0001151991,0.0004129907,0.0005165699],"genre_scores_gemma":[0.9936109,0.0002769931,0.004254728,0.0001074199,0.0002367662,0.00029044,0.0002332173,0.00007716552,0.0009123487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9350053,"threshold_uncertainty_score":0.9999316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613082140021643,"score_gpt":0.2406295565747645,"score_spread":0.224498735174548,"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."}}