{"id":"W4280580584","doi":"10.1016/j.cjca.2022.05.015","title":"Heart Transplantation for Cardiac Amyloidosis: The Need for High-Quality Data to Improve Patient Selection","year":2022,"lang":"en","type":"letter","venue":"Canadian Journal of Cardiology","topic":"Amyloidosis: Diagnosis, Treatment, Outcomes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"","keywords":"Medicine; Cardiac amyloidosis; Selection (genetic algorithm); Amyloidosis; Transplantation; Heart transplantation; Quality (philosophy); Intensive care medicine; Cardiology; Internal medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01063263,0.0004786188,0.001981923,0.001420914,0.003083617,0.004824309,0.002568793,0.02875446,0.005781367],"category_scores_gemma":[0.06820271,0.0005906808,0.001744109,0.001410644,0.002970243,0.004680432,0.001987898,0.03535263,0.002825466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006850931,"about_ca_system_score_gemma":0.01315183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02784874,"about_ca_topic_score_gemma":0.04338034,"domain_scores_codex":[0.9879615,0.004238266,0.00244181,0.0008082024,0.003406341,0.001143881],"domain_scores_gemma":[0.9050916,0.04585561,0.003958826,0.003015448,0.02220857,0.01987004],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009829875,0.0000817285,0.008601665,0.000112526,0.00005361318,0.003462534,0.0002050753,0.0001640053,0.0002501176,0.003090822,0.9470644,0.0368153],"study_design_scores_gemma":[0.0009601993,0.0002072262,0.03478871,0.003272275,0.0002540931,0.01681461,0.002443389,0.004705049,0.0004743382,0.065113,0.8705945,0.0003726457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0006352689,0.0008881422,0.0002531313,0.9904732,0.006524572,0.00001374405,0.00006887697,0.00002122097,0.001121825],"genre_scores_gemma":[0.01429764,0.002862093,0.002143885,0.890161,0.08820385,0.00008821796,0.0002467927,0.00006239617,0.00193407],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9893674,"threshold_uncertainty_score":0.05623144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02643686399468766,"score_gpt":0.2824636347174434,"score_spread":0.2560267707227558,"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."}}