{"id":"W2101035019","doi":"10.1038/nature09837","title":"Initial genome sequencing and analysis of multiple myeloma","year":2011,"lang":"en","type":"article","venue":"Nature","topic":"Multiple Myeloma Research and Treatments","field":"Medicine","cited_by":1439,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"National Cancer Institute; Multiple Myeloma Research Foundation; National Human Genome Research Institute; National Institute on Aging; Leukaemia and Lymphoma Research; Broad Institute","keywords":"Biology; Multiple myeloma; Gene; Genome; Genetics; Massive parallel sequencing; Mutation; Cancer; Somatic cell; DNA sequencing; Germline mutation; Cancer research; Cancer genome sequencing; Computational biology; Whole genome sequencing; Immunology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001103094,0.0005299612,0.0007668754,0.00143817,0.0005451483,0.0007765176,0.0004543029,0.0009564665,0.001509296],"category_scores_gemma":[0.002219178,0.000331685,0.0009848108,0.001577002,0.0002052093,0.0002980059,0.0009932379,0.001144968,0.000998518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000916711,"about_ca_system_score_gemma":0.0009764628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006033359,"about_ca_topic_score_gemma":0.006993963,"domain_scores_codex":[0.9989744,0.0001259106,0.00005657316,0.0003102845,0.0004245242,0.0001082762],"domain_scores_gemma":[0.9990778,0.0002036358,0.00009205075,0.0001292533,0.0004102825,0.00008695704],"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":[0.001586916,0.0001990077,0.06447307,0.002359309,0.001255399,0.001885522,0.001031964,0.007075481,0.5901551,0.00392663,0.04131783,0.2847337],"study_design_scores_gemma":[0.000230015,0.000674381,0.3288533,0.0005338949,0.0009693371,0.003416852,0.0005001373,0.01407513,0.2126781,0.006588249,0.4313245,0.0001560525],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6173172,0.04036717,0.1157434,0.005815002,0.001335417,0.001020466,0.1970579,0.004605813,0.0167377],"genre_scores_gemma":[0.6245881,0.01854859,0.1762686,0.005188598,0.0003827783,0.0008620457,0.162047,0.001050234,0.01106402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006033359,"threshold_uncertainty_score":0.01199651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04615722236335353,"score_gpt":0.3260179922858882,"score_spread":0.2798607699225347,"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."}}