{"id":"W2436872059","doi":"","title":"Pulse: Transplant queues grow as donor numbers wane","year":2000,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Organ Donation and Transplantation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Queue; Waiting list; Transplantation; Medicine; Computer network; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003706281,0.0005486147,0.0004913023,0.001143434,0.003664944,0.009860242,0.001208868,0.01137002,0.06743146],"category_scores_gemma":[0.03163185,0.000404979,0.0004867082,0.002107191,0.001638248,0.006617512,0.002240317,0.01086534,0.01537505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004329454,"about_ca_system_score_gemma":0.008203406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01355947,"about_ca_topic_score_gemma":0.0239236,"domain_scores_codex":[0.9982022,0.0002119462,0.0001181801,0.000175729,0.0009093826,0.0003826182],"domain_scores_gemma":[0.9791293,0.005537611,0.001793248,0.0006056377,0.004062052,0.008872202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006560066,0.00002080359,0.002366882,0.00005093291,0.000005631904,0.000112971,0.0001149741,0.0000548147,0.00008117815,0.003050291,0.9634163,0.03065971],"study_design_scores_gemma":[0.0001621199,0.00006550166,0.01417603,0.0002780616,0.0000324956,0.0004521536,0.001377469,0.0008200684,0.0003298984,0.009614594,0.9726335,0.00005806219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005244186,0.002317088,0.001038468,0.918421,0.03955807,0.00002084376,0.0008515745,0.0007380011,0.03181072],"genre_scores_gemma":[0.128812,0.007615292,0.002730757,0.6741174,0.0777668,0.000101191,0.001686073,0.0007865623,0.1063839],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06743146,"threshold_uncertainty_score":0.2255807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004349817716289299,"score_gpt":0.2272632361203204,"score_spread":0.2229134184040311,"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."}}