{"id":"W2327994519","doi":"10.1136/oemed-2014-102362.116","title":"0311  Development of a predictive model for estimating gamma radiation exposures among Ontario uranium miners0311  Development of a predictive model for estimating gamma radiation exposures among Ontario uranium miners","year":2014,"lang":"en","type":"article","venue":"Occupational and Environmental Medicine","topic":"Radioactivity and Radon Measurements","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre","funders":"","keywords":"Statistics; Linear regression; Leverage (statistics); Outlier; Regression analysis; Uranium; Linear model; Mathematics; Nuclear medicine; Environmental science; Medicine; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001535466,0.0004529748,0.0007383593,0.0002520295,0.0007666684,0.000008651537,0.0001733611,0.0002882823,0.00005374878],"category_scores_gemma":[0.0003246058,0.0004006459,0.0001056383,0.00008707388,0.0003053743,0.0004743949,0.00007378767,0.0003381534,0.000001025819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520645,"about_ca_system_score_gemma":0.0008741661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695369,"about_ca_topic_score_gemma":0.02546602,"domain_scores_codex":[0.9961111,0.0001481892,0.001641222,0.0006143481,0.0009533843,0.0005317574],"domain_scores_gemma":[0.9974831,0.0006357245,0.001279967,0.0002212269,0.0001227012,0.0002572985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002173547,0.0004056085,0.6382503,0.000765082,0.0004246326,4.214724e-7,0.1392559,0.192576,0.006370155,0.00003224594,0.0008664599,0.01887964],"study_design_scores_gemma":[0.003361716,0.0002944601,0.4227582,0.0004958824,0.0001400774,8.145783e-7,0.001342311,0.5707123,0.0005580215,0.00006897819,0.00004918251,0.0002180484],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5505854,0.00003923453,0.4472702,0.00003765721,0.000261324,0.001558978,0.00008161236,0.0000196665,0.0001459633],"genre_scores_gemma":[0.7828185,0.000004085806,0.2143392,0.00006188302,0.0002301017,0.0009397255,0.0009892685,0.00003863683,0.0005786277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3781363,"threshold_uncertainty_score":0.9998446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05343575726116794,"score_gpt":0.3085161268631696,"score_spread":0.2550803696020016,"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."}}