{"id":"W4281681743","doi":"10.1145/3539668.3539678","title":"Are WiFi Backscatter Systems Ready for the Real World?","year":2022,"lang":"en","type":"article","venue":"GetMobile Mobile Computing and Communications","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Backscatter (email); Scalability; Computer science; Throughput; Range (aeronautics); Scale (ratio); Energy consumption; Real-time computing; Telecommunications; Computer network; Wireless; Database; 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005203968,0.0001651536,0.0002044323,0.000084924,0.001603393,0.0001184725,0.0009843382,0.00003621057,0.000008928364],"category_scores_gemma":[0.00001557684,0.0001533091,0.00005712978,0.0003882404,0.0001289714,0.00004406027,0.0006558274,0.0004575238,0.00000400905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000954929,"about_ca_system_score_gemma":0.00001471068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009519327,"about_ca_topic_score_gemma":0.00009066494,"domain_scores_codex":[0.9988793,0.0001687571,0.0003282325,0.0002005676,0.0001272658,0.0002958783],"domain_scores_gemma":[0.9966282,0.001588278,0.0001413775,0.001523771,0.00006271159,0.00005560768],"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":[0.000002266258,0.00003448892,0.001948205,0.00004193695,0.00005236231,4.09011e-7,0.0003144497,0.9760193,0.00003200592,0.00431757,0.008712913,0.008524109],"study_design_scores_gemma":[0.0001639575,0.0000254686,0.002559475,0.00004852891,0.00002994315,0.00001086503,0.001032541,0.7345064,0.000003833,0.00004670088,0.2613881,0.0001842104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7117448,0.1120713,0.09065334,0.003050088,0.009430739,0.009997141,0.0007389756,0.008013318,0.05430029],"genre_scores_gemma":[0.9944665,0.0004630225,0.001211168,0.0001036801,0.0001889206,0.002374529,0.00008625216,0.00005972317,0.001046248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2827216,"threshold_uncertainty_score":0.9996964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03397343362070529,"score_gpt":0.2741443554844477,"score_spread":0.2401709218637424,"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."}}