{"id":"W2789356670","doi":"10.1111/ejh.13059","title":"Screening and diagnostic clinical algorithm for paroxysmal nocturnal hemoglobinuria: Expert consensus","year":2018,"lang":"en","type":"article","venue":"European Journal Of Haematology","topic":"Complement system in diseases","field":"Immunology and Microbiology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Thrombosis and Atherosclerosis Research Institute","funders":"Alexion Pharmaceuticals","keywords":"Paroxysmal nocturnal hemoglobinuria; Medicine; Differential diagnosis; Delphi method; Consensus conference; Pediatrics; Case finding; Algorithm; Family medicine; Intensive care medicine; Pathology; Internal medicine; Artificial intelligence; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06257538,0.001281754,0.001225336,0.00643138,0.002321656,0.003028195,0.004550531,0.003042875,0.009289487],"category_scores_gemma":[0.08803962,0.0008329021,0.002394755,0.002173238,0.001331781,0.003482046,0.007084897,0.00316662,0.004075218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0050442,"about_ca_system_score_gemma":0.02124596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002268719,"about_ca_topic_score_gemma":0.003719808,"domain_scores_codex":[0.9366047,0.04291289,0.008486109,0.003189726,0.007411179,0.001395341],"domain_scores_gemma":[0.9390981,0.01576456,0.004948311,0.001938367,0.035334,0.002916763],"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":[0.001281052,0.001846899,0.0322446,0.007959904,0.0005315662,0.002702955,0.01855323,0.01778282,0.007584883,0.03100585,0.1994672,0.6790389],"study_design_scores_gemma":[0.004100302,0.003395233,0.0601083,0.02060137,0.001509308,0.01187541,0.02882331,0.2622807,0.01198209,0.1863688,0.4078959,0.001059221],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0603033,0.003110574,0.7326611,0.04676513,0.001783917,0.1044932,0.002625333,0.001878437,0.04637907],"genre_scores_gemma":[0.08900522,0.0009727845,0.8848816,0.001961387,0.0002195066,0.0184902,0.001671392,0.00007760245,0.002720341],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06257538,"threshold_uncertainty_score":0.3309342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04960305646498333,"score_gpt":0.3326228675057923,"score_spread":0.283019811040809,"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."}}