{"id":"W2327200604","doi":"10.1021/ac301421k","title":"Automated Liquid–Liquid Extraction by Pneumatic Recirculation on a Centrifugal Microfluidic Platform","year":2012,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Chemistry; Microfluidics; Extraction (chemistry); Liquid–liquid extraction; Chromatography; Process (computing); Process engineering; Hexadecane; Nanotechnology; Materials science; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001223396,0.0002199814,0.000199581,0.0000352009,0.00009218176,0.00002713195,0.0001253157,0.0002325483,0.0005800061],"category_scores_gemma":[0.00003141704,0.0002266675,0.00009617393,0.0002551586,0.00003178576,0.0001442231,0.0000138184,0.0002729301,0.000290548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002774135,"about_ca_system_score_gemma":0.00002059716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004093982,"about_ca_topic_score_gemma":2.441648e-8,"domain_scores_codex":[0.9987466,0.000009625639,0.0003384074,0.0002001851,0.0002202422,0.0004849177],"domain_scores_gemma":[0.9993263,0.0000578227,0.00004259184,0.0003024013,0.00003279232,0.0002380645],"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":[0.00003499854,0.00008237455,0.00002256996,0.0000620496,0.00004735555,8.307245e-7,0.00002327668,0.00001175178,0.849323,0.0001461839,0.1501778,0.00006777598],"study_design_scores_gemma":[0.0001880674,0.00004034198,0.0001192857,0.00002894832,0.00006264523,0.00003037019,0.00002539961,0.005591284,0.9446383,0.000008953275,0.04900446,0.0002619153],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770921,0.01238502,0.00213755,0.00009025638,0.00006979905,0.0001331097,0.000021002,0.0008098708,0.007261329],"genre_scores_gemma":[0.9931472,0.006042163,0.0000107084,0.00006920502,0.0001758798,0.00003090906,0.0002506877,0.00004204621,0.0002312341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011734,"threshold_uncertainty_score":0.924323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00977294011166393,"score_gpt":0.2379201125621144,"score_spread":0.2281471724504504,"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."}}