{"id":"W4402740924","doi":"10.1063/5.0215567","title":"Microfluidic supercritical CO2 applications: Solvent extraction, nanoparticle synthesis, and chemical reaction","year":2024,"lang":"en","type":"article","venue":"Biomicrofluidics","topic":"Phase Equilibria and Thermodynamics","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Canada First Research Excellence Fund; Canada Research Chairs; Canada Foundation for Innovation; University of Alberta","keywords":"Supercritical fluid; Microfluidics; Nanotechnology; Supercritical fluid extraction; Materials science; Nanomaterials; Nanoparticle; Chemistry; Organic chemistry","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":[0.0001487312,0.0001853308,0.0001594863,0.00009704584,0.00006510576,0.0001196522,0.00009619861,0.0001541909,0.00002647654],"category_scores_gemma":[0.00002058238,0.0001950911,0.00006440432,0.0002085126,0.0001131682,0.0002306026,0.00003226418,0.0001617772,0.0001526618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149412,"about_ca_system_score_gemma":0.00003430351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000757709,"about_ca_topic_score_gemma":3.340281e-7,"domain_scores_codex":[0.9990252,0.00001859239,0.0002693439,0.0002879607,0.0001114952,0.000287436],"domain_scores_gemma":[0.9994708,0.000140323,0.000004634708,0.0002177134,0.00002596305,0.000140514],"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":[0.000008644588,0.00004122331,0.00002257204,0.000144246,0.00004803395,0.00001103779,0.00004230056,2.569014e-7,0.984058,0.003492842,0.004997121,0.007133754],"study_design_scores_gemma":[0.0001081698,0.000009002055,0.00004282552,0.00005568281,0.00006333063,0.0001573724,0.00003367817,0.004467898,0.8790967,0.0007087054,0.1150465,0.0002100635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9325711,0.05727179,0.008057262,0.0002588462,0.0004625973,0.0002307279,0.00005609983,0.0007739902,0.0003175695],"genre_scores_gemma":[0.9852728,0.01408144,0.0001399386,0.00003230952,0.0002408026,0.0001224578,0.00002884531,0.0000628791,0.00001850473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1100494,"threshold_uncertainty_score":0.7955584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009331375403991368,"score_gpt":0.2394102331862447,"score_spread":0.2300788577822533,"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."}}