{"id":"W4413055524","doi":"10.1038/s43018-025-01006-0","title":"SWIFT-seq enables comprehensive single-cell transcriptomic profiling of circulating tumor cells in multiple myeloma and its precursors","year":2025,"lang":"en","type":"article","venue":"Nature Cancer","topic":"Multiple Myeloma Research and Treatments","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"National Cancer Institute","keywords":"Circulating tumor cell; Multiple myeloma; Malignancy; Bone marrow; Computational biology; Cancer research; Biology; RNA-Seq; Transcriptome; Medicine; Pathology; Internal medicine; Immunology; Gene; Metastasis; Cancer; Gene expression; Genetics","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":[0.0002405828,0.0002343487,0.0004899288,0.0002682295,0.0003720286,0.0008937679,0.000274941,0.0003921343,0.001586477],"category_scores_gemma":[0.0003967289,0.0002151848,0.0003043555,0.0002764131,0.0001613783,0.0002459633,0.0004932755,0.0008451946,0.0006938176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002103992,"about_ca_system_score_gemma":0.0004298933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001692073,"about_ca_topic_score_gemma":0.005071255,"domain_scores_codex":[0.9997715,0.00001362992,0.000009932571,0.000102827,0.00007180887,0.00003025321],"domain_scores_gemma":[0.9998547,0.000048619,0.00001500724,0.00001745335,0.00004060887,0.00002359133],"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":[0.0002308719,0.00002448444,0.003586476,0.0001221248,0.00004085886,0.00008632186,0.000115435,0.0007461169,0.9764774,0.000473423,0.001916424,0.01618013],"study_design_scores_gemma":[0.000100947,0.0004061858,0.07925979,0.00007207022,0.0002491254,0.0009727931,0.0005002161,0.04668336,0.8032712,0.003948956,0.06443912,0.00009627116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8234391,0.003667957,0.1325054,0.0006160686,0.000384948,0.000195659,0.03082192,0.0026047,0.005764195],"genre_scores_gemma":[0.8775671,0.00192122,0.08405817,0.001101816,0.0001464777,0.0003739976,0.02575863,0.0008781638,0.008194529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001692073,"threshold_uncertainty_score":0.005307257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02664657689814045,"score_gpt":0.305176710401668,"score_spread":0.2785301335035276,"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."}}