{"id":"W2004450415","doi":"10.3390/s150101785","title":"Pose Estimation with a Kinect for Ergonomic Studies: Evaluation of the Accuracy Using a Virtual Mannequin","year":2015,"lang":"en","type":"article","venue":"Sensors","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Association Nationale de la Recherche et de la Technologie","keywords":"Kinematics; Software; Set (abstract data type); Computer science; Elbow; Shoulder joint; Simulation; Human–computer interaction; Joint (building); Artificial intelligence; Computer vision; 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":[0.002812176,0.001785172,0.0009494813,0.001662958,0.0002950018,0.0008309852,0.0008880926,0.0009671246,0.001796313],"category_scores_gemma":[0.008127861,0.0003605981,0.0006220114,0.000604914,0.0004833438,0.0008185909,0.001325537,0.0003461153,0.0007097722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001873739,"about_ca_system_score_gemma":0.0004436644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002140122,"about_ca_topic_score_gemma":0.002865356,"domain_scores_codex":[0.9974469,0.0009009363,0.0002095762,0.0004509676,0.0008579431,0.0001336828],"domain_scores_gemma":[0.9975371,0.001156364,0.0002311896,0.0003352838,0.0005500295,0.0001900075],"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":[0.005529081,0.00118795,0.08894785,0.002314822,0.0006735109,0.0007780578,0.001452997,0.08125152,0.3292291,0.00119032,0.002635301,0.4848095],"study_design_scores_gemma":[0.0002766085,0.005579918,0.3723245,0.000435662,0.0004207025,0.002047856,0.001048661,0.482674,0.1281925,0.001338032,0.005300752,0.0003607183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7425259,0.001517652,0.2495031,0.0001948644,0.0002791196,0.0004099911,0.001476518,0.001521307,0.002571453],"genre_scores_gemma":[0.9144782,0.0003896747,0.08244797,0.00007132538,0.00003565577,0.0002958352,0.001114817,0.0001548182,0.001011692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002812176,"threshold_uncertainty_score":0.01487237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.168798734683502,"score_gpt":0.4230680754612982,"score_spread":0.2542693407777962,"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."}}