{"id":"W189067298","doi":"10.22260/isarc2013/0118","title":"Dynamic Biomechanical Simulation for Identifying Risk Factors for Work-Related Musculoskeletal Disorders During Construction Tasks","year":2013,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work-related musculoskeletal disorders; Musculoskeletal disorder; Work (physics); Motion capture; Computer science; Motion (physics); Simulation; Physical medicine and rehabilitation; Engineering; Human factors and ergonomics; Artificial intelligence; Medicine; Poison control; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003275669,0.0001849792,0.0002721634,0.0001653277,0.0002442653,0.00003260935,0.000125125,0.0001789739,0.00003388209],"category_scores_gemma":[0.001390084,0.0001280968,0.000508961,0.0003456142,0.0001724112,0.0002788792,0.00004938555,0.0001737576,0.00000373865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001029303,"about_ca_system_score_gemma":0.00001612704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000320383,"about_ca_topic_score_gemma":0.000002009061,"domain_scores_codex":[0.9986817,0.00001165437,0.0004796867,0.0003103954,0.0002466066,0.0002699343],"domain_scores_gemma":[0.9987493,0.0003137735,0.0003884762,0.0001142434,0.0003563163,0.00007789555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008025328,0.000529988,0.1857728,0.01129115,0.0007714452,2.347734e-8,0.003347954,0.001137653,0.7525754,0.002543008,0.0002248751,0.04100315],"study_design_scores_gemma":[0.008143815,0.000732768,0.8440034,0.0009586496,0.0006283798,0.000002467096,0.005584441,0.09432097,0.009994744,0.03499224,0.00009992781,0.0005382507],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929832,0.00003620761,0.002343932,0.0006306365,0.000376967,0.003455888,0.00001091423,0.00008186747,0.00008044011],"genre_scores_gemma":[0.9951845,0.00001269092,0.004320533,0.000008942348,0.00004178637,0.0001988073,0.00002088649,0.00003874523,0.0001730746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7425807,"threshold_uncertainty_score":0.5223634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093382357546235,"score_gpt":0.2828036198917029,"score_spread":0.2718697963162405,"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."}}