{"id":"W4405035210","doi":"10.1182/blood-2024-200529","title":"Expanding the Eureka Study: Integrating a Comprehensive Clinical Registry with Molecular Profiling to Advance AL Amyloidosis Research","year":2024,"lang":"en","type":"article","venue":"Blood","topic":"Amyloidosis: Diagnosis, Treatment, Outcomes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Profiling (computer programming); Medicine; Amyloidosis; Internal medicine; 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":[0.03689941,0.0007718446,0.00136728,0.004926455,0.0004414342,0.004104983,0.001657473,0.001029881,0.004706775],"category_scores_gemma":[0.03204868,0.0004876546,0.001312186,0.006629717,0.0004962443,0.004117132,0.004651537,0.001375251,0.001897266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001711655,"about_ca_system_score_gemma":0.004594963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006154269,"about_ca_topic_score_gemma":0.003997779,"domain_scores_codex":[0.9820238,0.01072367,0.002627791,0.002341903,0.00137619,0.00090666],"domain_scores_gemma":[0.9604695,0.01043568,0.008062499,0.008097131,0.009303601,0.003631591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003581248,0.0005984951,0.8482091,0.001171455,0.001227014,0.0006012107,0.000649599,0.002216778,0.001321803,0.004645154,0.0315468,0.1042314],"study_design_scores_gemma":[0.002612158,0.0006651247,0.8767072,0.002326365,0.001037124,0.001305689,0.0008686219,0.003796187,0.001058023,0.00497783,0.1045358,0.0001098857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7519811,0.02611591,0.04612635,0.01736381,0.002408388,0.005743802,0.1116432,0.0007337439,0.03788381],"genre_scores_gemma":[0.812504,0.007559032,0.07163661,0.005864974,0.001691963,0.00618811,0.09164531,0.0006508898,0.002259204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03689941,"threshold_uncertainty_score":0.195145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04602649382874621,"score_gpt":0.4084199665629971,"score_spread":0.3623934727342508,"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."}}