{"id":"W2890678350","doi":"10.23889/ijpds.v3i4.1011","title":"Data linkage to build detailed return-to-work trajectories for work disability research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Workers' compensation; Workforce; Work (physics); Context (archaeology); Population; Business; Compensation (psychology); Medicine; Actuarial science; Psychology; Environmental health; Economics; Engineering; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09310119,0.001280503,0.002392848,0.01624323,0.0030739,0.005106541,0.004342809,0.002273707,0.02179648],"category_scores_gemma":[0.2772559,0.001370882,0.003423029,0.0278121,0.0008495095,0.003912645,0.008990734,0.002887668,0.003764934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00681374,"about_ca_system_score_gemma":0.04424255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2399147,"about_ca_topic_score_gemma":0.2193534,"domain_scores_codex":[0.9100696,0.04560202,0.018479,0.01006226,0.0126134,0.003173776],"domain_scores_gemma":[0.8056498,0.06208219,0.02420066,0.05023025,0.05469694,0.00314015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009094145,0.0005671434,0.338878,0.01487119,0.008151205,0.0004257224,0.006826981,0.008987377,0.0007878077,0.03777397,0.309734,0.2720872],"study_design_scores_gemma":[0.0008481424,0.0004580255,0.2636051,0.02259743,0.004702605,0.0003611005,0.005870444,0.0170043,0.001940978,0.04856235,0.6335043,0.000545294],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0469582,0.007038711,0.2105737,0.01506628,0.001683503,0.01724742,0.6690781,0.002330207,0.0300239],"genre_scores_gemma":[0.2172979,0.00355441,0.3596388,0.005746687,0.0005045417,0.04993456,0.3554018,0.0009948469,0.006926483],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2399147,"threshold_uncertainty_score":0.492372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4821570186123421,"score_gpt":0.6399370753878652,"score_spread":0.1577800567755231,"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."}}