{"id":"W2027805450","doi":"10.1016/j.prevetmed.2015.04.006","title":"Dealing with deficient and missing data","year":2015,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Missing data; Imputation (statistics); Population; Computer science; Disease; Data mining; Risk analysis (engineering); Data science; Statistics; Medicine; Mathematics; Machine learning; Environmental health; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001426137,0.0001207898,0.0002309345,0.00009427912,0.0005598672,0.000003804815,0.0001818675,0.00006805988,0.0001838523],"category_scores_gemma":[0.0003690571,0.00008904452,0.000007263538,0.0001331767,0.0001661514,0.0001906445,0.0003838728,0.0003167815,0.00003645945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000586008,"about_ca_system_score_gemma":0.0001454921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004037787,"about_ca_topic_score_gemma":0.00006758562,"domain_scores_codex":[0.9984316,0.000359239,0.0003381049,0.0003150055,0.0002487458,0.0003073699],"domain_scores_gemma":[0.9986905,0.0002752771,0.0001621943,0.0004271936,0.0001384221,0.0003064179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00695308,0.0009423234,0.4456567,0.007553717,0.000597136,0.00113653,0.2649338,0.0001099172,0.002114113,0.1221118,0.06470338,0.08318755],"study_design_scores_gemma":[0.01520107,0.01098056,0.1488833,0.01084205,0.000540312,0.0003925195,0.07613738,0.01105853,0.00001012876,0.02011519,0.7047604,0.001078625],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572964,0.003741172,0.005542221,0.01290637,0.0008978356,0.001073969,0.00007060762,0.0001359593,0.01833548],"genre_scores_gemma":[0.9942602,0.0001069178,0.004112367,0.0007276902,0.0002707681,0.00002086962,0.0001267602,0.00001619053,0.000358245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.640057,"threshold_uncertainty_score":0.4306102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6560469664248832,"score_gpt":0.5583610602287411,"score_spread":0.09768590619614215,"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."}}