{"id":"W3169986066","doi":"10.1111/hae.14364","title":"Converting factor and nonfactor usage into a single metric to facilitate benchmarking the resources consumed for haemophilia care across jurisdictions and over time","year":2021,"lang":"en","type":"article","venue":"Haemophilia","topic":"Hemophilia Treatment and Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Benchmarking; Metric (unit); Per capita; Medicine; Benchmark (surveying); Health care; Haemophilia; Population; Environmental health; Operations management; Environmental economics; Marketing; Economic growth; Business; Pediatrics; Economics; Geography","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":[0.01605536,0.001162357,0.000902408,0.007674527,0.0005066773,0.00262037,0.001146294,0.0005295022,0.004820526],"category_scores_gemma":[0.08535966,0.0003250795,0.001921523,0.01220506,0.0006286348,0.001782028,0.001535528,0.0009888253,0.001422039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001928359,"about_ca_system_score_gemma":0.002660355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01352157,"about_ca_topic_score_gemma":0.01102293,"domain_scores_codex":[0.9776571,0.009886964,0.003552007,0.001861332,0.006545419,0.0004972164],"domain_scores_gemma":[0.9529815,0.01653074,0.01076617,0.005207676,0.01395417,0.000559827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004834482,0.0003977222,0.6249103,0.001087199,0.001165612,0.0001513732,0.00202086,0.01058396,0.001566129,0.007075048,0.02285178,0.3277066],"study_design_scores_gemma":[0.00009308349,0.001479462,0.8368872,0.0008706095,0.0003627403,0.000696663,0.003777499,0.04723696,0.0102262,0.009611388,0.08849844,0.0002598363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6247407,0.002989017,0.2865316,0.001748222,0.0007564015,0.003207423,0.0329408,0.002925694,0.04416029],"genre_scores_gemma":[0.7380323,0.0008280089,0.241943,0.00029206,0.0001062592,0.002312002,0.01377529,0.0004463702,0.002264636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01605536,"threshold_uncertainty_score":0.08490986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05413311288556167,"score_gpt":0.3249033879628116,"score_spread":0.2707702750772499,"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."}}