{"id":"W2151645324","doi":"10.1080/15459624.2015.1072630","title":"Retrospective Exposure Assessment for Occupational Disease of an Individual Worker Using an Exposure Database and Trend Analysis","year":2015,"lang":"en","type":"article","venue":"Journal of Occupational and Environmental Hygiene","topic":"Occupational and environmental lung diseases","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Ontario Ministry of Labour; Workplace Safety & Insurance Board","funders":"National Institute for Occupational Safety and Health","keywords":"Occupational exposure; Exposure assessment; Environmental health; Occupational safety and health; Occupational disease; Medicine; Database; Computer science; Pathology","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":[0.008884988,0.0002779955,0.0006553355,0.004777321,0.0004378254,0.001403359,0.0006421617,0.000382493,0.0007074852],"category_scores_gemma":[0.01534851,0.0003609631,0.0006544436,0.004954169,0.0002441865,0.001318473,0.0009972303,0.0005014756,0.0002934386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007493465,"about_ca_system_score_gemma":0.001411583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008180892,"about_ca_topic_score_gemma":0.01002949,"domain_scores_codex":[0.9931571,0.001853331,0.001497755,0.0009043866,0.002415379,0.0001720452],"domain_scores_gemma":[0.9902142,0.003430149,0.002084773,0.001708787,0.00241413,0.0001481359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003327137,0.0001665972,0.75747,0.0004298209,0.0002936478,0.000264208,0.0007725338,0.01118046,0.006734713,0.004084893,0.002111121,0.2161593],"study_design_scores_gemma":[0.0000433407,0.0008055436,0.8967831,0.0003087259,0.0003496273,0.0009795041,0.0009635607,0.05371254,0.009814999,0.004008341,0.03211372,0.0001171943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5344453,0.002193401,0.4278952,0.00058835,0.00006055711,0.002767914,0.02314704,0.0008368777,0.008065251],"genre_scores_gemma":[0.5939474,0.001694405,0.3744258,0.0001177817,0.00007916453,0.00220613,0.02548574,0.000096997,0.001946643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008884988,"threshold_uncertainty_score":0.04698884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05396979449875162,"score_gpt":0.3352354856169819,"score_spread":0.2812656911182302,"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."}}