{"id":"W4366827876","doi":"10.1002/cjce.24918","title":"Droplet splitting in multi‐furcating microchannel: A three‐dimensional numerical simulation study","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Electronics and Information technology; Indian Council of Medical Research","keywords":"Microchannel; Volume of fluid method; Dimensionless quantity; Mechanics; Breakup; Volumetric flow rate; Channel (broadcasting); Flow (mathematics); Capillary number; Materials science; Ranging; Aspect ratio (aeronautics); Capillary action; Open-channel flow; Geometry; Physics; Thermodynamics; Mathematics; Electrical engineering; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000268972,0.0003020597,0.0005588495,0.0003744701,0.0005992739,0.0007053851,0.0005837716,0.001105017,0.001384078],"category_scores_gemma":[0.0006213028,0.0002282734,0.000675507,0.0004369675,0.0005531028,0.0003893935,0.0003775965,0.0004162184,0.0001053626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007742572,"about_ca_system_score_gemma":0.0008822856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01128571,"about_ca_topic_score_gemma":0.005025628,"domain_scores_codex":[0.999892,0.00001852608,0.000005972998,0.00001873161,0.00003462639,0.00003022464],"domain_scores_gemma":[0.999551,0.0002652013,0.00005293166,0.00003237246,0.00006221042,0.00003630571],"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":[0.00005566073,0.00009063841,0.002851817,0.00005639821,0.00002140096,0.0001868487,0.00008631449,0.9820784,0.01095822,0.001659875,0.0001115479,0.001842978],"study_design_scores_gemma":[0.000007163679,0.00001825529,0.0003388935,0.000002540381,0.000003400018,0.00001075226,0.0000137131,0.9981975,0.001184299,0.00009725981,0.0001208002,0.000005462228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714192,0.000161316,0.0226581,0.0001496047,0.00002692362,0.00005382252,0.0002422463,0.00009388237,0.00519496],"genre_scores_gemma":[0.9885385,0.0001186626,0.01005058,0.00002720327,0.00000537306,0.0000747626,0.0001315521,0.00001765577,0.001035689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01128571,"threshold_uncertainty_score":0.02244002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123560455154226,"score_gpt":0.2461733275857127,"score_spread":0.2249377230341705,"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."}}