{"id":"W3201751051","doi":"10.1039/d1lc00680k","title":"An automated centrifugal microfluidic assay for whole blood fractionation and isolation of multiple cell populations using an aqueous two-phase system","year":2021,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Fractionation; Chromatography; Microfluidics; Polyethylene glycol; PEG ratio; Biomedical engineering; Whole blood; Extraction (chemistry); Chemistry; Microfluidic chip; Materials science; Nanotechnology; Biochemistry; Surgery","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":[0.0001269713,0.0001262754,0.0001588521,0.000123515,0.0001231382,0.00004320332,0.00005143086,0.0001391633,0.000002716269],"category_scores_gemma":[0.00004812819,0.0001339191,0.00003264996,0.0001781851,0.00002074945,0.0001537308,0.00001107788,0.00008627973,0.000001305171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006364311,"about_ca_system_score_gemma":0.00002511509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005033363,"about_ca_topic_score_gemma":0.00001637347,"domain_scores_codex":[0.9992699,0.00005196525,0.000240884,0.0001958522,0.00008994466,0.0001514591],"domain_scores_gemma":[0.9995198,0.00004891046,0.00007175525,0.0002131232,0.0001044311,0.00004193298],"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":[0.0000171676,0.0001998598,0.0007546291,0.000114112,0.00001508092,0.000004537205,0.0000958306,0.001895422,0.9954609,0.000204268,0.0001420029,0.001096188],"study_design_scores_gemma":[0.001026515,0.00006748554,0.0004349791,0.0000475435,0.00004113158,0.00002248048,0.0002026745,0.4755031,0.5223643,0.00002775307,0.0001626239,0.0000995056],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9376879,0.0008898446,0.05980589,0.00002235694,0.0001907158,0.0002099705,0.0001390065,0.001025135,0.00002912987],"genre_scores_gemma":[0.9820955,0.00002813879,0.01743262,0.00001051313,0.00004809619,0.000004416751,0.000344967,0.00002700878,0.000008758818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4736076,"threshold_uncertainty_score":0.5461063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469590403774444,"score_gpt":0.2799515273880385,"score_spread":0.2552556233502941,"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."}}