{"id":"W3164664391","doi":"10.51510/trekritel.v1i1.412","title":"Perancangan Antena Mikrostrip Dual Band Profil Rendah Menggunakan Teknik DGS Dan Meander Line Untuk Aplikasi GNSS","year":2021,"lang":"en","type":"article","venue":"Teknologi Rekayasa Jaringan Telekomunikasi (TRekRiTel)","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"GNSS applications; GLONASS; Microstrip antenna; Multi-band device; Computer science; Physics; Electrical engineering; Antenna (radio); Global Positioning System; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001954222,0.0003873314,0.0002994904,0.000295301,0.0002338333,0.0009713096,0.0003716155,0.0005577211,0.004710428],"category_scores_gemma":[0.0002469328,0.0001530897,0.000205278,0.0002972075,0.0002678672,0.0004582801,0.0004055116,0.0004102847,0.002995761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002873563,"about_ca_system_score_gemma":0.0002734264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003348952,"about_ca_topic_score_gemma":0.0004897516,"domain_scores_codex":[0.9997746,0.00002925728,0.00001161651,0.00005404422,0.0001016548,0.0000288091],"domain_scores_gemma":[0.99981,0.00003357392,0.00002367139,0.00002987354,0.00008573892,0.0000170791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003641909,0.00006971614,0.005353562,0.0003674508,0.00003969621,0.0007382425,0.0004002906,0.01267863,0.3840487,0.00856137,0.0049684,0.5824097],"study_design_scores_gemma":[0.00007224645,0.001780097,0.01556843,0.0001572044,0.0001422307,0.008013558,0.0008854357,0.1054804,0.4876167,0.004457121,0.3756944,0.0001321624],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3233393,0.002550544,0.5906359,0.0007107323,0.0003620702,0.00007779369,0.0003349829,0.003200311,0.07878829],"genre_scores_gemma":[0.7543781,0.001324844,0.173223,0.0002333223,0.00007731827,0.00008681595,0.000526016,0.0002571859,0.06989332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004710428,"threshold_uncertainty_score":0.01575798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721212460953309,"score_gpt":0.2214778690176349,"score_spread":0.2042657444081019,"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."}}