{"id":"W3207511569","doi":"10.23977/jeis.2021.060205","title":"Research and Application of Intelligent Robot Electronic Coach System Based on AI Technology","year":2021,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coaching; Robot; Engineering; Electronics; Control (management); Position (finance); Computer science; Electrical engineering; Business; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003283591,0.0003517435,0.0003640089,0.0006095872,0.0004030877,0.0007717572,0.0007251104,0.0006270865,0.002492953],"category_scores_gemma":[0.0005045473,0.0001724911,0.0003630482,0.000528655,0.0003595443,0.001144279,0.0003400822,0.0003662151,0.000541441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709095,"about_ca_system_score_gemma":0.0006680447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00224292,"about_ca_topic_score_gemma":0.001002051,"domain_scores_codex":[0.9996516,0.00004914085,0.00001924831,0.00008336372,0.0001560868,0.00004054034],"domain_scores_gemma":[0.9997619,0.00005800564,0.00001501303,0.00001997979,0.0001224275,0.00002269961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003845757,0.0003907627,0.00872396,0.0009973875,0.0001428632,0.0007775893,0.0008688884,0.03866449,0.1723387,0.02442321,0.007164946,0.7451226],"study_design_scores_gemma":[0.0001616617,0.002409715,0.01928034,0.000224759,0.0002584501,0.001615198,0.0008470379,0.7769494,0.1016141,0.009925986,0.0865192,0.0001941657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1667276,0.01469459,0.7396883,0.00168689,0.0007291505,0.0003081339,0.0001066597,0.002364487,0.07369421],"genre_scores_gemma":[0.8872595,0.006098219,0.08044147,0.000352081,0.0002413401,0.0001930213,0.000151648,0.00004432518,0.02521844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002492953,"threshold_uncertainty_score":0.008339822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007316021954753917,"score_gpt":0.2729883024252248,"score_spread":0.2656722804704709,"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."}}