{"id":"W2048296660","doi":"10.1021/ac8021554","title":"Digital Microfluidic Method for Protein Extraction by Precipitation","year":2008,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canada Research Chairs","keywords":"Chemistry; Microfluidics; Precipitation; Lysis; Chromatography; Protein precipitation; Extraction (chemistry); Digital microfluidics; Lysis buffer; Protein purification; Nanotechnology; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004444138,0.000598846,0.0004557966,0.0007702873,0.000397444,0.0005134254,0.000899018,0.0005222532,0.002037367],"category_scores_gemma":[0.0004975176,0.0003125729,0.0003605084,0.00040471,0.0003791707,0.0005028426,0.000617602,0.0007367142,0.001085743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006470954,"about_ca_system_score_gemma":0.0005701334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003142459,"about_ca_topic_score_gemma":0.0004945236,"domain_scores_codex":[0.9994822,0.00004090522,0.00004692548,0.0001470858,0.0002419121,0.0000410336],"domain_scores_gemma":[0.9998097,0.00004748979,0.00004692743,0.00003588904,0.00004187771,0.00001815862],"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":[0.00006051079,0.00007233537,0.0003947718,0.0004551659,0.00004027452,0.00007801979,0.00004057793,0.0005969951,0.9297938,0.004553452,0.005437908,0.05847616],"study_design_scores_gemma":[0.00004585257,0.0002118035,0.001475122,0.00004306875,0.00005300043,0.0005639207,0.00001038447,0.008651159,0.8820195,0.001378621,0.1054874,0.00006005621],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07696608,0.01534554,0.8848535,0.001242283,0.002695456,0.0009649398,0.002465248,0.003698412,0.01176845],"genre_scores_gemma":[0.2547573,0.01036909,0.7114804,0.001350863,0.0005242553,0.001845173,0.002773207,0.0001600141,0.01673974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002037367,"threshold_uncertainty_score":0.006815732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00930320215484866,"score_gpt":0.2484098169545729,"score_spread":0.2391066147997242,"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."}}