{"id":"W2376661651","doi":"","title":"The Application of The Embedded Technology in Electrical Meter Reading","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automatic meter reading; Computer science; Mobile device; Reading (process); Microprocessor; Metre; Software; Electrical engineering; Electricity meter; Computer hardware; Embedded system; Power (physics); Telecommunications; Operating system; Wireless; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001868996,0.00007971331,0.00009882776,0.0001391252,0.00008363285,0.00001222026,0.0004983756,0.0001080126,2.892142e-7],"category_scores_gemma":[0.000001440797,0.00005203654,0.00003751121,0.0009472874,0.00007264289,0.00002209595,0.00007666572,0.0001830676,0.000009798348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006022253,"about_ca_system_score_gemma":0.000006785428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008201469,"about_ca_topic_score_gemma":0.00003781083,"domain_scores_codex":[0.9993363,0.000006165264,0.0002738043,0.0001225277,0.00005949239,0.0002016783],"domain_scores_gemma":[0.99942,0.00008022419,0.00004752596,0.0004132781,0.00002733615,0.00001164972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001964086,0.00003720105,0.003529396,0.00002120588,0.00002978789,2.945151e-7,0.0001288686,0.0002823858,0.2582238,0.1022264,0.0008633955,0.6346553],"study_design_scores_gemma":[0.0002429613,0.00001290672,0.01107447,0.00002077193,0.00001118834,0.0000270804,0.0001083972,0.009602337,0.3557496,0.01520047,0.6077403,0.0002095145],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0388158,0.0005366972,0.9583298,0.000335908,0.00002695799,0.0007027756,0.000001688444,0.0003306131,0.0009197706],"genre_scores_gemma":[0.9857301,0.00001668852,0.01385791,0.00001407942,0.00002712115,0.0003188885,0.00000101735,0.00001189277,0.00002237835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9469143,"threshold_uncertainty_score":0.2121988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003077998777235984,"score_gpt":0.2112480408370271,"score_spread":0.2081700420597911,"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."}}