{"id":"W4308364989","doi":"10.26508/lsa.202201543","title":"Myeloma immunoglobulin rearrangement and translocation detection through targeted capture sequencing","year":2022,"lang":"en","type":"article","venue":"Life Science Alliance","topic":"Multiple Myeloma Research and Treatments","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Calgary; University Health Network; University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Ontario Institute for Cancer Research; Princess Margaret Cancer Foundation","keywords":"Somatic hypermutation; Biology; Chromosomal translocation; Multiple myeloma; Immunoglobulin heavy chain; Antibody; Immunoglobulin gene; Gene rearrangement; Concordance; Bone marrow; DNA sequencing; Immunoglobulin light chain; Molecular biology; Gene; Cancer research; Genetics; B cell; Immunology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000450774,0.0001116026,0.0001464374,0.00006516591,0.0007657474,0.00004384948,0.0001289807,0.0000240158,0.0001296156],"category_scores_gemma":[0.000146728,0.0001003833,0.00003392196,0.0008159769,0.0002585253,0.0003154867,0.00006985368,0.0002170946,0.00001841428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004460914,"about_ca_system_score_gemma":0.0004142837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004198435,"about_ca_topic_score_gemma":0.00003540532,"domain_scores_codex":[0.9981869,0.00005015157,0.0001714601,0.0004220864,0.0007985473,0.000370879],"domain_scores_gemma":[0.9993787,0.0000211522,0.0000581042,0.0002653358,0.00009453022,0.0001821347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004790724,0.0001280188,0.007181579,0.00006793533,0.0000586633,0.0000858483,0.003983463,0.0003167049,0.9489689,0.0001620217,0.0002079116,0.03835991],"study_design_scores_gemma":[0.009557188,0.002264719,0.5251028,0.000238066,0.0001172747,0.0006815614,0.01164704,0.02828676,0.392031,0.000784915,0.02844625,0.0008424709],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920226,0.003068764,0.001188547,0.001742279,0.0001444125,0.0006532817,0.00001342621,0.00006861834,0.001098074],"genre_scores_gemma":[0.9959472,0.0002923136,0.002520178,0.0005753869,0.00004351681,0.0001391919,0.00001353085,0.000009749392,0.0004589212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5569379,"threshold_uncertainty_score":0.5889587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509366537565328,"score_gpt":0.3035197939090226,"score_spread":0.2684261285333693,"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."}}