{"id":"W4313546132","doi":"10.1111/ijlh.14016","title":"Defining ferritin clinical decision limits to improve diagnosis and treatment of iron deficiency: A modified Delphi study","year":2023,"lang":"en","type":"article","venue":"International Journal of Laboratory Hematology","topic":"Iron Metabolism and Disorders","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Women's College Hospital; St. Joseph’s Healthcare Hamilton; Hamilton Regional Laboratory Medicine Program; Alberta Medical Association; Toronto East General Hospital; University of Toronto; St. John’s Health Sciences Centre; Ottawa Hospital; Health Sciences Centre; Hamilton Health Sciences; Dalhousie University; Newfoundland and Labrador Centre for Applied Health Research; St. Michael's Hospital; Sunnybrook Health Science Centre; Mount Sinai Hospital; University of Calgary","funders":"","keywords":"Delphi method; Ferritin; Medicine; Likert scale; Iron deficiency; CLARITY; Intensive care medicine; Family medicine; Pediatrics; Psychology; Anemia; Psychiatry; Pathology; 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":[0.1253062,0.0009278777,0.0008138472,0.002335727,0.002841108,0.002620338,0.001558746,0.001932392,0.002965797],"category_scores_gemma":[0.1337354,0.0009245565,0.00185122,0.001244124,0.003383717,0.003051533,0.008248431,0.00238775,0.0003836233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007729176,"about_ca_system_score_gemma":0.01159981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003273336,"about_ca_topic_score_gemma":0.004051491,"domain_scores_codex":[0.8834571,0.1008036,0.005785096,0.001884615,0.00424844,0.00382112],"domain_scores_gemma":[0.8586417,0.115692,0.004857622,0.003203156,0.01530164,0.002303873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.004337821,0.003583253,0.07105736,0.007698525,0.0006177782,0.001267039,0.6629013,0.005657312,0.004156147,0.01482605,0.008050795,0.2158465],"study_design_scores_gemma":[0.003722095,0.0142804,0.1094969,0.008176412,0.0008452266,0.00145703,0.7513284,0.03283723,0.007072384,0.02538228,0.04456334,0.0008383091],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9496949,0.0003647475,0.01702466,0.002701304,0.0001012451,0.02122149,0.000224473,0.00003545699,0.008631649],"genre_scores_gemma":[0.9451557,0.000372407,0.02532025,0.001142105,0.00002442242,0.02717092,0.0001377191,0.00001353978,0.0006628021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1253062,"threshold_uncertainty_score":0.6626905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274264502832413,"score_gpt":0.3939643451070646,"score_spread":0.3512217000787405,"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."}}