{"id":"W2588782734","doi":"10.1093/annweh/wxw026","title":"Predicting Directly Measured Trunk and Upper Arm Postures in Paper Mill Work From Administrative Data, Workers’ Ratings and Posture Observations","year":2016,"lang":"en","type":"article","venue":"Annals of Work Exposures and Health","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Vetenskapsrådet; Canada Research Chairs","keywords":"Inclinometer; Trunk; Work (physics); Statistics; Akaike information criterion; Physical medicine and rehabilitation; Mathematics; Physical therapy; Computer science; Psychology; Medicine; Engineering; Geodesy; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006861055,0.001213056,0.0007359715,0.001254608,0.0002986128,0.001182945,0.0008123596,0.0008196856,0.001195218],"category_scores_gemma":[0.0187152,0.000672813,0.001458015,0.0008546836,0.000376144,0.000682528,0.0008052391,0.0006956888,0.0007935177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005882137,"about_ca_system_score_gemma":0.0008899023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01049724,"about_ca_topic_score_gemma":0.01438246,"domain_scores_codex":[0.9972838,0.001665441,0.000138989,0.0005217189,0.0002733828,0.0001165718],"domain_scores_gemma":[0.9852585,0.01076942,0.001940836,0.0009356905,0.0008003614,0.0002951843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006834323,0.0005241476,0.9082785,0.0001359696,0.0005553372,0.00009379713,0.0005084861,0.05180434,0.002609946,0.00009802659,0.0003128898,0.03439503],"study_design_scores_gemma":[0.00005042967,0.001254292,0.6939791,0.00006240884,0.0001722782,0.00009153553,0.0004395422,0.3018735,0.001315375,0.0004211526,0.0002832472,0.0000571237],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756508,0.0001203518,0.02326694,0.00005382569,0.00001266898,0.00006573927,0.0004459257,0.0001103038,0.0002734673],"genre_scores_gemma":[0.9879065,0.0000808743,0.01073256,0.00001772161,0.00001111862,0.0001018182,0.0008131497,0.00001211562,0.000324163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01049724,"threshold_uncertainty_score":0.03628516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358859756572581,"score_gpt":0.3738050137991152,"score_spread":0.2379190381418571,"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."}}