{"id":"W2954441056","doi":"10.22260/isarc2019/0004","title":"3D Posture Estimation from 2D Posture Data for Construction Workers","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimation; Computer science; Joint (building); Productivity; Download; Engineering; World Wide Web; Structural engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005263945,0.001297973,0.001019244,0.003115217,0.0003228219,0.0007192834,0.0006324551,0.001127367,0.002947889],"category_scores_gemma":[0.00172999,0.0005413489,0.001034065,0.001821535,0.000274903,0.0004795115,0.00134149,0.0005557844,0.003871466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003031641,"about_ca_system_score_gemma":0.0005569909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006417026,"about_ca_topic_score_gemma":0.01266454,"domain_scores_codex":[0.9993963,0.00009893178,0.00003895824,0.0001797193,0.0002016034,0.00008443116],"domain_scores_gemma":[0.9991583,0.0001779194,0.0001224383,0.0001636142,0.0003138079,0.00006389344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001125475,0.0004796745,0.08044888,0.001129121,0.0004357373,0.0007972257,0.0005321639,0.02857652,0.08688974,0.0004274124,0.01715191,0.7820063],"study_design_scores_gemma":[0.0001092588,0.0006297759,0.4453347,0.0005107786,0.00021236,0.001776374,0.001029504,0.494006,0.03504683,0.002572254,0.01854524,0.0002269744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3115869,0.00305086,0.6473678,0.0003126186,0.0004017151,0.0004594026,0.02698648,0.006673749,0.003160352],"genre_scores_gemma":[0.6830812,0.001579467,0.2703292,0.0001160752,0.0001739975,0.0006873793,0.04084576,0.0002975664,0.002889378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006417026,"threshold_uncertainty_score":0.01275939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613565798342739,"score_gpt":0.2816656545589573,"score_spread":0.2655299965755299,"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."}}