{"id":"W4408124558","doi":"10.2139/ssrn.5119868","title":"When Less is More: Optimizing Prescription Alerts under Fatigue","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medical prescription; Computer science; Medical emergency; Medicine; Nursing","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001170762,0.0003830264,0.0005989979,0.0004894708,0.00028354,0.00004666262,0.0003800013,0.001025621,0.00003745452],"category_scores_gemma":[0.00008462329,0.0003630117,0.0002719291,0.000150796,0.00007909582,0.0001007165,0.0002872009,0.01103386,0.000007885662],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002748004,"about_ca_system_score_gemma":0.006858027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003896159,"about_ca_topic_score_gemma":0.0001885,"domain_scores_codex":[0.9960591,0.0001309777,0.0006364944,0.0005184943,0.0004441464,0.002210797],"domain_scores_gemma":[0.998574,0.000048543,0.000367229,0.0005844713,0.0002656335,0.0001601384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0017252,0.001061746,0.1144613,0.00396798,0.007503907,0.0002216111,0.009597545,0.004683302,0.0007606711,0.08535317,0.01118104,0.7594825],"study_design_scores_gemma":[0.008340931,0.002689424,0.009009789,0.01787447,0.002808696,0.003786552,0.02258501,0.004350266,0.00735686,0.9055848,0.01290695,0.002706278],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7179716,0.03450308,0.1805372,0.05408719,0.006574559,0.001967235,0.00003654014,0.0007078421,0.003614783],"genre_scores_gemma":[0.9670003,0.01964678,0.002271421,0.001165309,0.001138274,0.00005652904,0.00006393998,0.00005552143,0.008601912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8202316,"threshold_uncertainty_score":0.9998822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06195507878078853,"score_gpt":0.3479509470625095,"score_spread":0.2859958682817209,"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."}}