{"id":"W2965662949","doi":"10.1109/isie.2019.8781248","title":"A Low-Cost Battery Charger Usable with Sinusoidal Ripple-Current and Pulse Charging Algorithms for E-Bike Applications","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Battery charger; Electrical engineering; Ripple; Voltage; Battery (electricity); Amplifier; Computer science; Converters; Power (physics); Waveform; Electronic engineering; Engineering; CMOS; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000882935,0.0001977713,0.0002003829,0.0001558141,0.00008155649,0.00006387841,0.0002189574,0.00007175204,0.0002101494],"category_scores_gemma":[0.00001036673,0.0001637609,0.00002993048,0.000239721,0.0000608945,0.0002613432,0.00008648694,0.0002483108,0.0001545688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009085126,"about_ca_system_score_gemma":0.00001513811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002812258,"about_ca_topic_score_gemma":0.00000585359,"domain_scores_codex":[0.9987974,0.000004658436,0.0001649823,0.0003420124,0.0001669063,0.0005240144],"domain_scores_gemma":[0.9993228,0.0001073261,0.00002280814,0.0004055057,0.00006060381,0.0000809893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005821559,0.0001533195,0.009337962,0.001291944,0.0001100952,0.000004043676,0.0001215061,0.008093797,0.02342134,0.00172582,0.002853912,0.952828],"study_design_scores_gemma":[0.004512853,0.000285852,0.00418282,0.0003643022,0.000039433,0.00007361855,0.0005994677,0.5141821,0.1351756,0.001422438,0.3371877,0.001973829],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08473837,0.000262116,0.9096202,0.0003361737,0.0001123504,0.002739013,0.0000985667,0.0008747543,0.001218437],"genre_scores_gemma":[0.9699184,0.0001853352,0.02379434,0.0001050224,0.0001569007,0.003762275,0.0001034571,0.0001378659,0.001836356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9508542,"threshold_uncertainty_score":0.6677977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751360252373645,"score_gpt":0.2709427278778735,"score_spread":0.253429125354137,"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."}}