{"id":"W3202223316","doi":"10.1109/access.2021.3118207","title":"EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation Using Accelerated Neuroevolution With Weight Transfer","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Nvidia","keywords":"Neuroevolution; Computer science; Artificial intelligence; Computer vision; Pose; Artificial neural network","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001404801,0.000116636,0.0001321635,0.00008929324,0.0007042618,0.00122001,0.000459733,0.00004462388,0.00007814281],"category_scores_gemma":[0.0000133809,0.00008671766,0.00004461057,0.0005699174,0.0001084289,0.002404483,0.00004956732,0.0001507259,0.000007546786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003641692,"about_ca_system_score_gemma":0.0001763148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001514131,"about_ca_topic_score_gemma":0.0001933498,"domain_scores_codex":[0.9989175,0.0001243093,0.0002418167,0.0002672524,0.0002816877,0.0001674447],"domain_scores_gemma":[0.9992124,0.00004528519,0.00008874692,0.0003226183,0.0002957271,0.00003522401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001635959,0.001006974,0.003440575,0.0004568406,0.0004068505,0.000274634,0.01049843,0.03598429,0.7929184,0.04951142,0.002812759,0.1025253],"study_design_scores_gemma":[0.0009713994,0.0001002351,0.01144079,0.0002095099,0.000100847,0.0001676805,0.00008402498,0.1813618,0.7971326,0.006548536,0.001489385,0.0003932104],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6056301,0.00002487699,0.3932015,0.0002661844,0.0003291041,0.00009621045,0.00000251637,0.00005766259,0.0003918894],"genre_scores_gemma":[0.998208,0.000006405463,0.001367213,0.0002329612,0.0001053064,0.000006715744,0.00001360217,0.00001039312,0.0000493411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.392578,"threshold_uncertainty_score":0.9998168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06159348470675086,"score_gpt":0.3150131397487581,"score_spread":0.2534196550420073,"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."}}