{"id":"W2753662912","doi":"10.3390/s17092003","title":"Wearable Devices for Classification of Inadequate Posture at Work Using Neural Networks","year":2017,"lang":"en","type":"article","venue":"Sensors","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Chicoutimi","funders":"Fonds de recherche du Québec – Nature et technologies; Université du Québec à Chicoutimi","keywords":"Wearable computer; Inertial measurement unit; Artificial neural network; Context (archaeology); Computer science; Artificial intelligence; Identification (biology); Center of pressure (fluid mechanics); Wearable technology; Work (physics); Set (abstract data type); Machine learning; Pattern recognition (psychology); Engineering; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001199832,0.0001009844,0.0001525845,0.00003399362,0.0002246185,0.00003107309,0.0001896885,0.0001240509,0.00003441698],"category_scores_gemma":[0.00003014297,0.00009622175,0.0001016838,0.00003862962,0.00008920526,0.00005366019,0.00003930135,0.00008129919,0.00001191553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002416301,"about_ca_system_score_gemma":0.000006698016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002717684,"about_ca_topic_score_gemma":0.0003547599,"domain_scores_codex":[0.9992982,0.00003340098,0.0001757996,0.0002138598,0.00004610184,0.0002326496],"domain_scores_gemma":[0.9991331,0.00005225716,0.0002802724,0.0004449224,0.00004718093,0.00004233687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003944878,0.0005707176,0.6023584,0.0004169726,0.001026885,0.00001426517,0.004874603,0.1147934,0.01297051,0.02983852,0.01012789,0.219063],"study_design_scores_gemma":[0.0006497458,0.00006504111,0.9101631,0.00003330758,0.00004941318,0.000001911477,0.0004331594,0.08532801,0.00002447825,0.0001867857,0.002888486,0.0001765683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921361,0.0003273022,0.0001166544,0.0004642702,0.000747257,0.0002514348,0.000007485473,0.00001448477,0.005935013],"genre_scores_gemma":[0.9978622,0.00001497717,0.0002168482,0.00006604527,0.0001070078,0.000009718789,0.00001074928,0.00002243552,0.001690058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3078047,"threshold_uncertainty_score":0.3923809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05316670051248282,"score_gpt":0.337243856335103,"score_spread":0.2840771558226201,"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."}}