{"id":"W4393174576","doi":"10.1049/icp.2023.2539","title":"Demonstration of longitudinal power profile estimation using commercial transceivers and its practical consideration","year":2023,"lang":"en","type":"article","venue":"IET conference proceedings.","topic":"Advanced Electrical Measurement Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Transceiver; Computer science; Power (physics); Estimation; Electrical engineering; Electronic engineering; Engineering; Telecommunications; Systems engineering; Wireless","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":[0.001090755,0.0004877216,0.000219081,0.0003367108,0.0003182422,0.0006328027,0.0007552386,0.0007443626,0.002295296],"category_scores_gemma":[0.002447549,0.0002769484,0.0001616335,0.0005003907,0.000337421,0.0009298057,0.0006075777,0.0006786734,0.0009313648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003507035,"about_ca_system_score_gemma":0.0005571019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008977233,"about_ca_topic_score_gemma":0.001395177,"domain_scores_codex":[0.99939,0.0001396607,0.00002940833,0.0001103301,0.0002531925,0.00007744797],"domain_scores_gemma":[0.9978524,0.0007336541,0.000337402,0.0003821738,0.0006192686,0.00007513874],"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":[0.0003979165,0.0002828286,0.01090579,0.0001938752,0.00005460205,0.0007143366,0.0003172096,0.006370336,0.8876628,0.005379783,0.004336199,0.08338438],"study_design_scores_gemma":[0.00004213784,0.0005996822,0.005370807,0.00002843702,0.00002580457,0.001153463,0.0001097889,0.1320424,0.8527077,0.001019951,0.006848915,0.0000507577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4112791,0.0004513773,0.5736474,0.00107873,0.0001542612,0.0001347795,0.0003419401,0.003724671,0.009187693],"genre_scores_gemma":[0.9021742,0.0001271503,0.09519171,0.0001855576,0.00004984465,0.00006358929,0.0001533204,0.0001173612,0.001937404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002295296,"threshold_uncertainty_score":0.007678509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07740865956979764,"score_gpt":0.3210831070232227,"score_spread":0.2436744474534251,"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."}}