{"id":"W4390638019","doi":"10.1177/20543581231221891","title":"High-Throughput Computing to Automate Population-Based Studies to Detect the 30-Day Risk of Adverse Outcomes After New Outpatient Medication Use in Older Adults with Chronic Kidney Disease: A Clinical Research Protocol","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Kidney Health and Disease","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Victoria Hospital; Western University; London Health Sciences Centre","funders":"National Institute of General Medical Sciences","keywords":"Medicine; Medical prescription; Population; Cohort; Kidney disease; Cohort study; Health care; Prescription drug; Pharmacy; Emergency medicine; Family medicine; Internal medicine; Environmental health; Pharmacology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07875193,0.003084261,0.002285993,0.00312587,0.004399793,0.003462254,0.005254281,0.00376624,0.0166797],"category_scores_gemma":[0.07488895,0.002219629,0.005361587,0.003772746,0.002182487,0.001797073,0.003984291,0.003355229,0.005197762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007344353,"about_ca_system_score_gemma":0.06530668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01099885,"about_ca_topic_score_gemma":0.01545861,"domain_scores_codex":[0.9426328,0.03676255,0.009166445,0.003018755,0.006599975,0.001819531],"domain_scores_gemma":[0.9246613,0.01762346,0.007561525,0.01109553,0.0338105,0.00524763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.07832275,0.01540993,0.04008237,0.05817678,0.005062838,0.002521849,0.004865817,0.0314892,0.009835349,0.03826451,0.2179306,0.4980381],"study_design_scores_gemma":[0.1615244,0.03688176,0.06093741,0.02504012,0.005174549,0.001260582,0.001866155,0.02877477,0.01684809,0.02203996,0.6388569,0.0007952882],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.002360784,0.0002795241,0.01956262,0.0006491964,0.0001561886,0.969272,0.005092215,0.0001705426,0.002457029],"genre_scores_gemma":[0.002309856,0.0002236748,0.02330648,0.0002492445,0.00003522517,0.9724564,0.0010154,0.00001044995,0.0003933645],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.07875193,"threshold_uncertainty_score":0.416485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06546967003708071,"score_gpt":0.4284947432283092,"score_spread":0.3630250731912285,"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."}}