{"id":"W3092224556","doi":"10.1016/j.ebiom.2020.103031","title":"A liquid biopsy for detecting circulating mesothelial precursor cells: A new biomarker for diagnosis and prognosis in mesothelioma","year":2020,"lang":"en","type":"article","venue":"EBioMedicine","topic":"Occupational and environmental lung diseases","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; Princess Margaret Cancer Centre; University of Toronto; University Health Network; Toronto General Hospital; Ontario Institute for Cancer Research","funders":"National Cancer Institute; Princess Margaret Cancer Foundation","keywords":"Mesothelin; Mesothelioma; Biomarker; Liquid biopsy; Medicine; Flow cytometry; Mesothelial Cell; Population; Pathology; CD90; Biopsy; Circulating tumor cell; Asbestos; CD34; Cancer research; Immunology; Cancer; Internal medicine; Biology; Stem cell","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001921839,0.0001958123,0.0003491705,0.0001488019,0.00007040069,0.0000122335,0.0000679281,0.00009682989,0.0001389511],"category_scores_gemma":[0.0006067653,0.0001617826,0.0001080723,0.0003040678,0.00008054534,0.0000666753,0.00004451772,0.00006871846,0.000006498499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005209129,"about_ca_system_score_gemma":0.00007887606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005925142,"about_ca_topic_score_gemma":0.000008102215,"domain_scores_codex":[0.998645,0.00001802266,0.0003655908,0.0004119455,0.0002718008,0.0002876281],"domain_scores_gemma":[0.9990365,0.0003298576,0.00009555384,0.0000885862,0.00002620322,0.000423297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01122483,0.000813384,0.5044093,0.003124736,0.0003962972,0.0001281386,0.002626576,0.00000824355,0.3201443,0.00005327734,0.005326415,0.1517445],"study_design_scores_gemma":[0.05577291,0.02091224,0.6200711,0.005274877,0.002048439,0.0002968706,0.002167023,0.04196476,0.2037805,0.0005732166,0.04530166,0.001836434],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818174,0.00151711,0.001368664,0.0128841,0.0001149168,0.002033025,0.0001279432,0.00007112414,0.00006569304],"genre_scores_gemma":[0.991944,0.00006430044,0.004958006,0.001618891,0.000641472,0.0005698453,0.00008411441,0.00004662849,0.00007276385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1499081,"threshold_uncertainty_score":0.6597304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04496902429021575,"score_gpt":0.2971477629044712,"score_spread":0.2521787386142554,"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."}}