{"id":"W2481456694","doi":"10.1021/acs.analchem.6b01324","title":"Combination of Mechanical and Molecular Filtration for Enhanced Enrichment of Circulating Tumor Cells","year":2016,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; McGill University; McGill University and Génome Québec Innovation Centre","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Lloyd Carr-Harris Foundation; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs","keywords":"Circulating tumor cell; Chemistry; Epithelial cell adhesion molecule; Filtration (mathematics); Size-exclusion chromatography; Receptor; Antibody; Flow cytometry; Epidermal growth factor receptor; Cancer cell; Cell; Cancer; Molecular biology; Chromatography; Cancer research; Metastasis; Biochemistry; Immunology; Biology","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":[0.00009975911,0.00005647411,0.0001935777,0.0000116701,0.000007822401,0.000001725471,0.00002158636,0.00003728713,0.00008518543],"category_scores_gemma":[0.0001264977,0.00004168127,0.00007269326,0.00005011724,0.00004052507,0.00001535174,0.00001176061,0.00002602064,2.886491e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002613593,"about_ca_system_score_gemma":0.00003460653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003760506,"about_ca_topic_score_gemma":1.485341e-7,"domain_scores_codex":[0.9994328,0.000004491751,0.0002188075,0.0001311059,0.0001311002,0.00008167236],"domain_scores_gemma":[0.9995635,0.00008095907,0.00008439074,0.000106101,0.0001046625,0.00006035955],"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":[0.0000563201,0.00008014427,0.00003546508,0.0003404582,0.00003702409,0.000001248413,0.000008686488,8.316945e-7,0.9965083,0.0006369128,0.00003344267,0.00226114],"study_design_scores_gemma":[0.00113072,0.00009322246,0.00008347307,0.00009869724,0.0001492112,0.000002992222,0.00002189449,0.00054705,0.9972694,0.0004779211,0.00008092904,0.00004451089],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651387,0.0000476443,0.03322411,0.0002890535,0.0000131419,0.0001338156,0.00001684441,0.000005295507,0.00113141],"genre_scores_gemma":[0.9985711,0.00001429954,0.001212859,0.00003699406,0.00001905278,0.000007721997,0.000008855082,0.00000550019,0.0001236462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03343239,"threshold_uncertainty_score":0.1699713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234247565645423,"score_gpt":0.2714463650655654,"score_spread":0.2591038894091112,"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."}}