{"id":"W2891442307","doi":"10.23889/ijpds.v3i4.839","title":"Development of an automated system for clinical study recruitment","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; CLs upper limits; Medical emergency; Emergency medicine; Analytics; Creatinine; Database; Internal medicine; Computer science","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":[0.03359274,0.002017436,0.001964316,0.007648845,0.001887141,0.006443796,0.004362989,0.001817422,0.02904051],"category_scores_gemma":[0.07360456,0.00218991,0.00139837,0.004454565,0.0008825786,0.004418519,0.005355091,0.003001014,0.0193638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002587622,"about_ca_system_score_gemma":0.009537388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004541876,"about_ca_topic_score_gemma":0.002715342,"domain_scores_codex":[0.9727687,0.008230725,0.00545565,0.006083286,0.006424618,0.001037077],"domain_scores_gemma":[0.9087992,0.03883516,0.0061302,0.01375502,0.02699798,0.00548256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00183466,0.0009783955,0.02450197,0.001082241,0.0003544221,0.0007454776,0.001090166,0.00428777,0.01529342,0.005517809,0.2243976,0.7199161],"study_design_scores_gemma":[0.003758133,0.001999492,0.03664141,0.00108456,0.0005369351,0.001480609,0.000884712,0.294995,0.07235093,0.01761093,0.5678039,0.0008532199],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01331101,0.0005609352,0.6540637,0.003464862,0.001285182,0.01538505,0.0152173,0.2885477,0.00816426],"genre_scores_gemma":[0.07850462,0.0003582315,0.8660037,0.002516462,0.0009934893,0.01232398,0.02255294,0.004555482,0.01219107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03359274,"threshold_uncertainty_score":0.1776575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3431685655831244,"score_gpt":0.5074725869746233,"score_spread":0.1643040213914989,"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."}}