{"id":"W3106556104","doi":"10.1007/978-3-030-62199-5_9","title":"Miniature 2.45 GHz Rectenna for Low Levels of Power","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rectenna; Electrical engineering; Microstrip; Microwave; Rectifier (neural networks); Engineering; Dissipation factor; Voltage; Power (physics); Electronic engineering; Antenna (radio); Renewable energy; Energy conversion efficiency; Materials science; Optoelectronics; Dielectric; Topology (electrical circuits); Telecommunications; Computer science; Physics; Rectification","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":[0.000123267,0.0004175718,0.0003164004,0.0002507004,0.0001588039,0.0006214636,0.0005332492,0.0006471697,0.008088491],"category_scores_gemma":[0.0001342834,0.0003666722,0.0002913561,0.0003441215,0.000188847,0.0008800644,0.0003776151,0.0005919136,0.004936558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001770187,"about_ca_system_score_gemma":0.00008181698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004019978,"about_ca_topic_score_gemma":0.0002136033,"domain_scores_codex":[0.9998906,0.000008550652,0.000003262119,0.00003566593,0.00004832277,0.00001376519],"domain_scores_gemma":[0.9999368,0.00001985252,0.00001090863,0.00001494383,0.00001232871,0.00000510067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006781959,0.00003843977,0.0001105618,0.0003339064,0.00002227245,0.0001126865,0.0001208183,0.0009180184,0.8875765,0.0122235,0.009505759,0.08896961],"study_design_scores_gemma":[0.00002541157,0.000500954,0.001476543,0.00009868811,0.00005207764,0.001854971,0.00007158805,0.01199161,0.534026,0.004541801,0.4453077,0.00005254789],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1295319,0.03419239,0.5485724,0.002755841,0.003121124,0.0001617807,0.0006072342,0.003712725,0.2773446],"genre_scores_gemma":[0.4483767,0.009124779,0.2196917,0.001106752,0.0006979185,0.0001561307,0.0004787475,0.0006207885,0.3197465],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008088491,"threshold_uncertainty_score":0.02705872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118752803907041,"score_gpt":0.1997437613555356,"score_spread":0.1885562333164652,"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."}}