{"id":"W2075296706","doi":"10.1063/1.4817792","title":"Field tested milliliter-scale blood filtration device for point-of-care applications","year":2013,"lang":"en","type":"article","venue":"Biomicrofluidics","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Tech University; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Grand Challenges Canada","keywords":"Whole blood; Filtration (mathematics); Point of care; Aspartate transaminase; Antibody; HBsAg; Hepatitis B; Alanine transaminase; Point-of-care testing; Biomedical engineering; Medicine; Chromatography; Materials science; Immunology; Chemistry; Internal medicine; Pathology; Hepatitis B virus; Enzyme; Biochemistry; Mathematics","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":[0.00005144535,0.0001638582,0.0001878883,0.0001029308,0.00007131926,0.00003395919,0.0002114851,0.0002380398,0.00002740971],"category_scores_gemma":[0.0000327689,0.000158004,0.00008788506,0.0002254367,0.00006326298,0.00009409616,0.00003604679,0.00008067284,0.00003777604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002705038,"about_ca_system_score_gemma":0.00001990538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002929879,"about_ca_topic_score_gemma":0.000002585492,"domain_scores_codex":[0.9991948,0.00000740896,0.0003143249,0.0001923629,0.00006609004,0.0002250307],"domain_scores_gemma":[0.9992565,0.0001110222,0.00004723042,0.0003736073,0.0001708262,0.0000408113],"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":[0.000004212977,0.00002635671,0.000403277,0.0002240828,0.00002338275,1.397843e-7,0.0001093277,5.492489e-7,0.9400994,0.00007603221,0.02556152,0.03347169],"study_design_scores_gemma":[0.0002730942,0.0001103499,0.0001664138,0.00003920212,0.00004486611,0.00000496344,0.0003306316,0.0002024249,0.9616274,0.000269415,0.03674782,0.0001833982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8518911,0.02080358,0.1225116,0.0005268517,0.0002811883,0.001945144,0.0002092621,0.001217978,0.0006132866],"genre_scores_gemma":[0.9761257,0.001302903,0.02188183,0.0001267073,0.00007712521,0.0002193376,0.000162594,0.00004012624,0.00006364616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1242346,"threshold_uncertainty_score":0.6443216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008276645465031002,"score_gpt":0.2111373443785712,"score_spread":0.2028606989135402,"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."}}