{"id":"W4385391472","doi":"10.1016/j.jmoldx.2023.05.002","title":"Genomic Data Heterogeneity across Molecular Diagnostic Laboratories","year":2023,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Taiho Pharmaceutical; TG Therapeutics; CTI Biopharma; Karyopharm Therapeutics; Sierra Oncology; Leukemia and Lymphoma Society; Bristol-Myers Squibb","keywords":"Computational biology; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001472243,0.0003034794,0.000670056,0.0002829125,0.0001215693,0.0001189888,0.001075744,0.0002161677,0.00002983554],"category_scores_gemma":[0.02196722,0.0002722823,0.0002112154,0.001180628,0.0002253329,0.0002082708,0.001066734,0.0008663154,0.0002001331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002911749,"about_ca_system_score_gemma":0.001007776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001704672,"about_ca_topic_score_gemma":0.00000637225,"domain_scores_codex":[0.9966488,0.0002014935,0.0008250726,0.0004072019,0.001153232,0.0007641998],"domain_scores_gemma":[0.9949806,0.001662482,0.0003810697,0.001447446,0.0009550331,0.0005733825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006471237,0.0009449045,0.268963,0.0007245224,0.002679609,0.1602762,0.0008448104,0.002856565,0.4016187,0.0008056873,0.1458626,0.01377634],"study_design_scores_gemma":[0.01264613,0.003101361,0.3303529,0.001345516,0.002120924,0.006147905,0.001200079,0.002307864,0.4910091,0.001835552,0.1463732,0.001559492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864475,0.005233216,0.003981434,0.002919886,0.0005134383,0.0003715985,0.0003947167,0.00006829211,0.00006993716],"genre_scores_gemma":[0.9858521,0.007998875,0.003611277,0.001620876,0.0004876673,0.00001057305,0.0002595568,0.0001218859,0.000037194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1541283,"threshold_uncertainty_score":0.9999729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03910317410278107,"score_gpt":0.3643692789306439,"score_spread":0.3252661048278628,"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."}}