{"id":"W4394944202","doi":"10.4322/rae.v15n2.e202115.en","title":"PRACTICES RELATED TO INDUSTRY 4.0 AND ITS APPLICATIONS IN THE FIELD OF ERGONOMICS: ANALYSIS OF APPLICATIONS OF COLLABORATIVE ROBOTS (COBOTS) AND EXOSKELETONS","year":2021,"lang":"en","type":"article","venue":"Revista Ação Ergonômica","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Robot; Exoskeleton; Field (mathematics); Human–computer interaction; Engineering; Human factors and ergonomics; Manufacturing engineering; Computer science; Simulation; Artificial intelligence; Poison control; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002023064,0.0000880348,0.0003032609,0.0001918298,0.00003073901,0.0000166421,0.00011683,0.000120506,0.00001082276],"category_scores_gemma":[0.0003126566,0.00007665752,0.00004577652,0.001911066,0.00004899211,0.00004884657,0.00004214081,0.0001680884,4.247544e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000014551,"about_ca_system_score_gemma":0.00005339206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000895912,"about_ca_topic_score_gemma":0.00003509769,"domain_scores_codex":[0.9991744,0.00006344626,0.0004431921,0.0001556287,0.00008170044,0.00008158907],"domain_scores_gemma":[0.99831,0.0009282972,0.0002242766,0.0002980085,0.0001973762,0.00004204733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00006786574,0.0008760568,0.04233055,0.002959786,0.002718254,0.000002804781,0.01678262,0.5517966,0.09837301,0.2729261,0.0005304698,0.01063584],"study_design_scores_gemma":[0.003302619,0.0009496113,0.5326056,0.001464513,0.009300411,0.00002845313,0.05459718,0.2279111,0.09393395,0.004497384,0.06875004,0.002659139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869544,0.005002005,0.005539948,0.000945235,0.00001188067,0.0008098104,0.0001350253,0.0000155396,0.0005861832],"genre_scores_gemma":[0.9958234,0.001018671,0.002978447,0.00002762523,0.00000383934,0.00008996508,0.00002061169,0.000008703336,0.00002876762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.490275,"threshold_uncertainty_score":0.3126003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009534995224595716,"score_gpt":0.2981269960913514,"score_spread":0.2885920008667557,"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."}}