{"id":"W4382365380","doi":"10.54941/ahfe1003627","title":"An overview of various tasks and trades in the construction industry offering potential for exoskeletons","year":2023,"lang":"en","type":"article","venue":"AHFE international","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Wearable computer; Construction industry; Wearable technology; Computer science; Occupational safety and health; Event (particle physics); Human factors and ergonomics; Engineering; Risk analysis (engineering); Computer security; Data science; Forensic engineering; Poison control; Construction engineering; Business; Simulation; Medical emergency; Medicine; Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008677208,0.00005594979,0.00009881031,0.0001644754,0.0002111903,0.00000801546,0.0001697959,0.0001493759,0.0001522834],"category_scores_gemma":[0.0002057019,0.00004447779,0.00002711228,0.0001876669,0.00006001686,0.0001165675,0.00003619742,0.0004312091,0.00001022299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004653905,"about_ca_system_score_gemma":0.0002156419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003517644,"about_ca_topic_score_gemma":0.0001671087,"domain_scores_codex":[0.9988769,0.000187364,0.0003220611,0.0001313546,0.0002734619,0.0002088934],"domain_scores_gemma":[0.9988976,0.0007463677,0.00008304239,0.00009939888,0.0001207045,0.00005288885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006890699,0.0002315627,0.6815912,0.001001379,0.00007526075,0.00001501331,0.005394387,0.0005637773,0.001418713,0.2055429,0.003979799,0.09949698],"study_design_scores_gemma":[0.0008374312,0.00009074971,0.9746948,0.0001119243,0.000004569914,0.000007802048,0.001996663,0.01067296,0.00001354074,0.007313504,0.004200956,0.00005511902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905182,0.00006973632,0.0004404434,0.006548541,0.000636925,0.0006497509,0.0001908008,0.00002309922,0.0009225717],"genre_scores_gemma":[0.9982895,0.0001876177,0.0004582571,0.0003076117,0.0002836043,0.0002133294,0.0001503796,0.000007275129,0.0001023923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2931036,"threshold_uncertainty_score":0.1873413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2116772303058398,"score_gpt":0.5410007979956611,"score_spread":0.3293235676898214,"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."}}