{"id":"W4386126086","doi":"10.32920/24026679","title":"Magnetic water-in-water droplet microfluidics: Systematic experiments and scaling mathematical analysis","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polyethylene glycol; Microfluidics; PEG ratio; Biocompatible material; Scaling; Materials science; Dextran; Ferrofluid; Nanotechnology; Phase (matter); Chemical engineering; Magnetic field; Aqueous two-phase system; Aqueous solution; Chemistry; Chromatography; Biomedical engineering; Organic chemistry; Engineering; Physics","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":[0.001635201,0.0006367156,0.0005044167,0.0004367624,0.0003247707,0.0004503463,0.0005873263,0.0004792808,0.0009328182],"category_scores_gemma":[0.003564272,0.0002662374,0.0004878871,0.0003158218,0.0008132682,0.0006672576,0.000505612,0.0005540987,0.0001380065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000633586,"about_ca_system_score_gemma":0.0007060987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001341976,"about_ca_topic_score_gemma":0.0008639704,"domain_scores_codex":[0.9996279,0.0001142871,0.00002273873,0.00008939685,0.0001218506,0.0000236463],"domain_scores_gemma":[0.9984389,0.0009806461,0.000234273,0.0001846075,0.0001365157,0.00002506423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001580641,0.0004605523,0.003927317,0.001225152,0.00013918,0.0003922692,0.0004275207,0.4618532,0.3096448,0.1479879,0.002062846,0.07172116],"study_design_scores_gemma":[0.00001966075,0.00005886005,0.0005345219,0.00001643083,0.0000117823,0.000026047,0.0000155883,0.9509771,0.03962124,0.007402777,0.001291823,0.00002419928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1520535,0.001141763,0.8405026,0.0004886398,0.00007836302,0.0004620471,0.000379795,0.0006703636,0.00422295],"genre_scores_gemma":[0.7060304,0.001464627,0.2884812,0.00009709278,0.00006899882,0.001021466,0.0002767523,0.0001871915,0.0023722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001635201,"threshold_uncertainty_score":0.008647859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251378884125223,"score_gpt":0.2570303789114919,"score_spread":0.2345165900702396,"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."}}