{"id":"W1978038422","doi":"10.1186/1472-6947-9-48","title":"Development of a validation algorithm for 'present on admission' flagging","year":2009,"lang":"en","type":"article","venue":"BMC Medical Informatics and Decision Making","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Health, State Government of Victoria; Australian Commission on Safety and Quality in Health Care","keywords":"Flagging; Medical diagnosis; Algorithm; Medicine; Kappa; Quality (philosophy); Flag (linear algebra); Quality assurance; Health informatics; Computer science; Medical emergency; Public health; Mathematics; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02995987,0.0011969,0.00135989,0.005362833,0.00154826,0.003130695,0.00347385,0.002297716,0.002694901],"category_scores_gemma":[0.09715291,0.0007616488,0.001444524,0.002963318,0.0007315619,0.00170006,0.001966392,0.002216849,0.002123198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001805209,"about_ca_system_score_gemma":0.006832214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01620297,"about_ca_topic_score_gemma":0.0111566,"domain_scores_codex":[0.9867491,0.004220943,0.002627305,0.003241356,0.00260235,0.0005589585],"domain_scores_gemma":[0.932798,0.02995816,0.004667556,0.004248995,0.02756992,0.000757311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008130449,0.0006549831,0.2223052,0.0005551143,0.0006497927,0.000394839,0.000863285,0.1045449,0.007389696,0.003481335,0.03794869,0.6203992],"study_design_scores_gemma":[0.0002466852,0.0002069594,0.02008069,0.0001992259,0.0001133575,0.0003817271,0.0002044195,0.9603401,0.006064195,0.003627279,0.008477015,0.00005841388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1033585,0.0005156662,0.8711094,0.0009356224,0.0003395511,0.002842154,0.005235154,0.01227263,0.003391299],"genre_scores_gemma":[0.1677672,0.00008841317,0.8212551,0.0003000821,0.00006116718,0.001143611,0.008232413,0.000267829,0.0008842064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02995987,"threshold_uncertainty_score":0.1584448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2741609628696525,"score_gpt":0.5092488686602057,"score_spread":0.2350879057905532,"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."}}