{"id":"W3047370150","doi":"10.1109/infocom41043.2020.9155452","title":"Reliable Backscatter with Commodity BLE","year":2020,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Goodput; Computer science; Backscatter (email); Telecommunications link; Channel (broadcasting); Network packet; Reliability (semiconductor); Interference (communication); Modulation (music); Electronic engineering; Real-time computing; Computer network; Telecommunications; Power (physics); Wireless; Throughput; 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":[],"consensus_categories":[],"category_scores_codex":[0.00002881215,0.0001010895,0.0001061869,0.000009171527,0.00002816236,0.00002794425,0.0001222571,0.00004466995,0.0003253452],"category_scores_gemma":[0.000004024682,0.00008339159,0.00001574242,0.0001384835,0.0000209297,0.00009072086,0.00002414408,0.0001619855,0.0001990838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001446196,"about_ca_system_score_gemma":0.000005377188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001603161,"about_ca_topic_score_gemma":0.0000234588,"domain_scores_codex":[0.9995186,0.00000548003,0.00008928376,0.0001159804,0.00008520104,0.0001854206],"domain_scores_gemma":[0.9996887,0.00002711973,0.000008574397,0.0001573268,0.00001545623,0.0001028517],"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":[0.000004284543,0.000004803941,0.003970393,0.00003469349,0.00001931083,0.000007434538,0.00005190439,0.8681157,0.0002886378,0.0005127359,0.12663,0.0003601758],"study_design_scores_gemma":[0.0004213424,0.00006865752,0.001470487,0.00004909794,0.00001438194,0.000007357957,0.00002336433,0.8528078,0.008121824,0.00004627888,0.1365845,0.0003849935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3177074,0.0002109243,0.1624756,0.003052068,0.0003773114,0.0001911885,0.000005841791,0.004562219,0.5114174],"genre_scores_gemma":[0.9861438,0.000009007541,0.01183069,0.001154855,0.000178243,0.00000790854,0.000008476187,0.00004183278,0.000625209],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6684363,"threshold_uncertainty_score":0.3562301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01182688676539495,"score_gpt":0.1697869752555174,"score_spread":0.1579600884901225,"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."}}