{"id":"W4412754967","doi":"10.11159/iccste25.284","title":"Exploring Vision-Based Technologies for Ergonomic Training in Construction Education","year":2025,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Computer science; Human–computer interaction; Artificial intelligence; Engineering management; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001058279,0.0003144458,0.0001848873,0.0006291677,0.0003387967,0.001244592,0.0003280534,0.0005818381,0.001838468],"category_scores_gemma":[0.002557539,0.0001727184,0.0002633684,0.0003611154,0.0004108143,0.001023294,0.000961017,0.0003264731,0.000266044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004419553,"about_ca_system_score_gemma":0.0008389289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001404426,"about_ca_topic_score_gemma":0.003307852,"domain_scores_codex":[0.9993277,0.0002934599,0.00002032465,0.00008329413,0.0001694135,0.0001058666],"domain_scores_gemma":[0.9991608,0.0005187709,0.00007553706,0.00003536464,0.0001268071,0.00008269575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004943738,0.002267364,0.06976771,0.001014745,0.00008975901,0.0004289303,0.01214508,0.007449179,0.09491352,0.003824834,0.001594405,0.8060102],"study_design_scores_gemma":[0.0003021422,0.01488232,0.672497,0.001825723,0.0004795229,0.002555615,0.05742961,0.1092799,0.06623031,0.01843267,0.05575157,0.0003335799],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144651,0.001002762,0.07435495,0.0006599505,0.00004416626,0.000247528,0.00006122833,0.0001501081,0.009014212],"genre_scores_gemma":[0.9593392,0.000601154,0.03860027,0.0001070948,0.00001075089,0.0001038369,0.00003319493,0.000007037974,0.001197317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001838468,"threshold_uncertainty_score":0.006150305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08178563807814113,"score_gpt":0.3779587619956748,"score_spread":0.2961731239175337,"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."}}