{"id":"W3107809658","doi":"10.18280/ria.340518","title":"Recognition of Wrong Sports Movements Based on Deep Neural Network","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demonstrative; Computer science; Artificial intelligence; Convolutional neural network; Computer vision; Perception; Graph; Psychology","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":[0.0001891817,0.0001323187,0.000165994,0.0000690238,0.0001091841,0.00005282699,0.0003360209,0.00005315213,0.0004913004],"category_scores_gemma":[0.00005110808,0.0001379206,0.0001038561,0.0005064994,0.00003191245,0.0002584268,0.00005449018,0.0001461294,0.0003499398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001812464,"about_ca_system_score_gemma":0.00001533951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004261948,"about_ca_topic_score_gemma":0.000001704624,"domain_scores_codex":[0.9986611,0.00005582849,0.0004124069,0.0003764617,0.0002505539,0.0002436535],"domain_scores_gemma":[0.9992144,0.00008811629,0.0001875516,0.0003007581,0.00009237621,0.0001168284],"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":[0.00004948469,0.0002086168,0.0005881981,0.0000726019,0.00001099066,0.00003126396,0.0007333268,0.4246708,0.001378201,0.001144061,0.0005551048,0.5705573],"study_design_scores_gemma":[0.0000486914,0.0002214805,0.000183436,0.00007346252,0.000005183032,0.000001960905,0.00007283528,0.9473101,0.04932673,0.001915999,0.0006933431,0.0001467977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06017245,0.00003911473,0.9304683,0.001114553,0.0004714876,0.0002762779,0.000004234445,0.0001500983,0.007303462],"genre_scores_gemma":[0.993739,0.00001309904,0.003859925,0.002104184,0.0001819533,0.00001263205,0.00001839877,0.00001041751,0.00006035379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9335666,"threshold_uncertainty_score":0.562424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05534893739355826,"score_gpt":0.2562718909518135,"score_spread":0.2009229535582552,"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."}}