{"id":"W4323798980","doi":"10.5281/zenodo.7706409","title":"3D Human Pose Estimation Via Deep Learning Methods","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wycliffe College","funders":"","keywords":"Pose; Artificial intelligence; Deep learning; Computer science; Estimation; Machine learning; Computer vision; Pattern recognition (psychology); Engineering","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":[0.0003917806,0.001258368,0.00071145,0.001155298,0.0002400482,0.0007109948,0.0008961944,0.0007915255,0.003724933],"category_scores_gemma":[0.001299239,0.0007099545,0.0008000908,0.0008297307,0.00043251,0.0008473195,0.00136328,0.0009473379,0.00210319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000454309,"about_ca_system_score_gemma":0.0005440183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00477047,"about_ca_topic_score_gemma":0.008135957,"domain_scores_codex":[0.9995248,0.00007723904,0.0000186007,0.0001626513,0.0001654714,0.0000511699],"domain_scores_gemma":[0.9996901,0.00007006288,0.00005554029,0.0000627781,0.0001006111,0.00002101624],"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":[0.0001553555,0.00005949875,0.002115926,0.0001328427,0.0001004517,0.0001579706,0.0001064133,0.2136442,0.02217093,0.003587353,0.005121935,0.7526471],"study_design_scores_gemma":[0.000007002672,0.00003676357,0.001486998,0.00002671968,0.00001176227,0.0001217796,0.00002063166,0.9860178,0.005489441,0.00352066,0.003241731,0.00001868999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005835821,0.0002250424,0.9912722,0.00004570053,0.00004846034,0.00002531846,0.0001429422,0.00122867,0.001175778],"genre_scores_gemma":[0.4760388,0.001242174,0.5081706,0.0003656993,0.0001680632,0.0001888725,0.001558442,0.0003778665,0.01188958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00477047,"threshold_uncertainty_score":0.01246113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05092975256801364,"score_gpt":0.3200230928070145,"score_spread":0.2690933402390009,"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."}}