{"id":"W2891423572","doi":"10.1587/transcom.2018nvi0002","title":"Technology and Standards Accelerating 5G Commercialization","year":2018,"lang":"en","type":"article","venue":"IEICE Transactions on Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"GLS Industries (Canada)","funders":"","keywords":"Computer science; Standardization; Radio access network; Enabling; Core network; Flexibility (engineering); Slicing; Cellular network; Commercialization; Telecommunications; Low latency (capital markets); Computer network; World Wide Web; Operating system; Mobile station; Base station","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":[0.002256044,0.0005280521,0.0002362455,0.001232134,0.0005558141,0.002457113,0.0006514247,0.001781525,0.00724919],"category_scores_gemma":[0.00386778,0.0002247954,0.0003382745,0.001637242,0.0009180239,0.004195204,0.001594061,0.002573437,0.00319945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812402,"about_ca_system_score_gemma":0.002569974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00402596,"about_ca_topic_score_gemma":0.002217356,"domain_scores_codex":[0.9986901,0.0002033852,0.00007620214,0.0001702932,0.0006830412,0.0001770104],"domain_scores_gemma":[0.9981522,0.0003193623,0.0001466037,0.0001702361,0.001073343,0.0001381846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008396422,0.00006883674,0.001977536,0.0004363628,0.00001840322,0.0003431686,0.0005682046,0.004767852,0.01211284,0.6429227,0.06223863,0.2744614],"study_design_scores_gemma":[0.00001515567,0.0001345652,0.001943605,0.0003985941,0.0000233228,0.0003764755,0.0003732654,0.006980943,0.004334501,0.07031012,0.9150768,0.00003262544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06339658,0.08006939,0.2493647,0.0968614,0.01143257,0.0003642185,0.001018593,0.001934138,0.4955584],"genre_scores_gemma":[0.4561749,0.1590956,0.2450002,0.01737306,0.008402471,0.0003552741,0.001854104,0.0004451319,0.1112993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00724919,"threshold_uncertainty_score":0.02425092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03036525387290621,"score_gpt":0.3018710113353233,"score_spread":0.2715057574624171,"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."}}