{"id":"W2314967240","doi":"10.1021/ac5022198","title":"Digital Microfluidic Platform for Human Plasma Protein Depletion","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Human serum albumin; Chromatography; Hemopexin; Blood proteins; Protein detection; Dilution; Microfluidics; Biomarker; Biochemistry; Nanotechnology; Enzyme","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":[0.00007308793,0.0001464021,0.000153106,0.0000238742,0.00006734833,0.00005651138,0.0001639934,0.0001827988,0.00001850701],"category_scores_gemma":[0.0001395934,0.0001459511,0.00008453606,0.00008187515,0.00006266114,0.00006370014,0.00002537885,0.0001800185,0.00002115217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005937241,"about_ca_system_score_gemma":0.000007702912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001007087,"about_ca_topic_score_gemma":1.711421e-7,"domain_scores_codex":[0.999244,0.000001141639,0.0001802464,0.000180658,0.00007689033,0.0003170757],"domain_scores_gemma":[0.9996531,0.00004008547,0.00001762944,0.0002066389,0.00002509094,0.00005745799],"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":[0.000004374504,0.00001393612,0.00006501681,0.0001457134,0.00002831448,8.138809e-7,0.000004158345,0.000002485745,0.9807217,0.0007279105,0.008231105,0.01005455],"study_design_scores_gemma":[0.0002718019,0.00003180378,0.000009288028,0.00003022129,0.00001582407,0.0000080694,0.00001493516,0.001467496,0.9361411,0.001523105,0.06030443,0.0001819565],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725116,0.0002357552,0.01132111,0.0001016961,0.00001776278,0.0001145224,0.00001227538,0.0009719526,0.0147133],"genre_scores_gemma":[0.9978323,0.00001071954,0.0001662017,0.00001171819,0.0001069359,0.00003588671,0.00006046981,0.00003050733,0.00174528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05207333,"threshold_uncertainty_score":0.5951712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008408020645342547,"score_gpt":0.2118179742304646,"score_spread":0.2034099535851221,"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."}}