{"id":"W3084092512","doi":"10.1111/jvim.15892","title":"An artificial neural network-based model to predict chronic kidney disease in aged cats","year":2020,"lang":"en","type":"article","venue":"Journal of Veterinary Internal Medicine","topic":"Veterinary Medicine and Surgery","field":"Veterinary","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"","keywords":"Medicine; CATS; Kidney disease; Artificial neural network; Creatinine; Predictive value; Population; Internal medicine; Machine learning; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007388904,0.0006879095,0.0004674795,0.0006281138,0.000344048,0.0007119855,0.0005818862,0.0007577658,0.002039193],"category_scores_gemma":[0.001809804,0.0002752788,0.0005768585,0.0003200025,0.0002003511,0.0003465105,0.0003934893,0.00053979,0.0002497035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001273276,"about_ca_system_score_gemma":0.001030856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03154545,"about_ca_topic_score_gemma":0.02404873,"domain_scores_codex":[0.9998627,0.00004348022,0.0000117409,0.00004322236,0.0000179574,0.00002079208],"domain_scores_gemma":[0.9993213,0.0004426281,0.00006375061,0.00001262744,0.0001292311,0.00003046223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001338727,0.00008641724,0.0173341,0.00003962213,0.0000808626,0.00008964282,0.00004727788,0.9701811,0.0005194971,0.0002353984,0.0003208406,0.01093127],"study_design_scores_gemma":[0.000005130362,0.00003291406,0.00158554,0.000006623852,0.00001019888,0.000009677121,0.000006607737,0.9980772,0.00005837203,0.0001321198,0.00007245331,0.000003205689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9063638,0.0005190297,0.08781842,0.0004847763,0.00008034962,0.0001554044,0.00104872,0.0003310857,0.003198441],"genre_scores_gemma":[0.9876743,0.0001060567,0.009948188,0.00004778968,0.00001240607,0.0001313691,0.0004880241,0.000009851544,0.001582019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03154545,"threshold_uncertainty_score":0.0627237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1256793492192951,"score_gpt":0.366734992506503,"score_spread":0.2410556432872079,"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."}}