{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005866884,0.000117858,0.0001209234,0.00001832133,0.000057633,0.00002261993,0.00009327629,0.0001574423,0.00001712774],"category_scores_gemma":[0.0001547681,0.0001223946,0.00006906025,0.0001035008,0.00004280769,0.00009677057,0.00001001797,0.0001604841,0.00001118505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006646544,"about_ca_system_score_gemma":0.00001472926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001479721,"about_ca_topic_score_gemma":2.0118e-8,"domain_scores_codex":[0.9993672,0.000002751582,0.0001603014,0.0001693071,0.00007538511,0.0002250009],"domain_scores_gemma":[0.9997154,0.00005336501,0.00001893981,0.000134668,0.00003411333,0.00004350243],"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":[0.000005815644,0.00001791635,0.00002145572,0.00005879537,0.00002620999,0.000001612108,0.000009155691,0.00000297678,0.9221996,0.00001532492,0.06766554,0.009975587],"study_design_scores_gemma":[0.0001577016,0.00001753078,0.000008174859,0.00001195404,0.00001338806,0.0000314639,0.00002457689,0.001391514,0.9469728,0.0001925402,0.05104158,0.0001367693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5032659,0.003311219,0.4838652,0.0002889237,0.00003545884,0.0002356674,0.00004917771,0.001249974,0.007698534],"genre_scores_gemma":[0.988593,0.0001378065,0.004205156,0.00001447968,0.00007386202,0.00007576626,0.0001130842,0.00003381767,0.006752986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4853272,"threshold_uncertainty_score":0.4991106,"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."}}