{"id":"W4242833011","doi":"10.32920/ryerson.14648724","title":"Numerical simulation of the effects of G-jitters on thermal diffusion process in binary and ternary mixtures","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Field-Flow Fractionation Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Ternary operation; Thermodynamics; Mass transfer; Diffusion; Buoyancy; Materials science; Heat transfer; Thermophoresis; Thermal; Binary number; Mechanics; Chemistry; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000367316,0.0002851798,0.0004604661,0.000380219,0.0004543012,0.0005084131,0.0004331165,0.0008332958,0.001443298],"category_scores_gemma":[0.001207113,0.0001824964,0.0003278327,0.0004868818,0.0006958509,0.0003371584,0.0003724521,0.0003849234,0.0001130155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005733676,"about_ca_system_score_gemma":0.0004824287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005703979,"about_ca_topic_score_gemma":0.002425234,"domain_scores_codex":[0.99988,0.00002469326,0.000007354641,0.00001906629,0.00003471346,0.0000341482],"domain_scores_gemma":[0.9992847,0.0004195427,0.00010504,0.00004415566,0.0001023699,0.00004422051],"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":[0.0002254097,0.00009275825,0.00227508,0.0001050056,0.00001823478,0.0001699269,0.0001192655,0.9629645,0.02615514,0.003480988,0.0002441732,0.004149458],"study_design_scores_gemma":[0.00001000228,0.00002560301,0.0002981439,0.000004009291,0.000003056974,0.000007944986,0.00001314404,0.9959028,0.003475084,0.0001364241,0.0001184452,0.000005192982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9638203,0.0003319804,0.0270627,0.0002756251,0.00007132497,0.00003671729,0.0002310228,0.0002385337,0.007931806],"genre_scores_gemma":[0.9914646,0.00008776694,0.007231544,0.00001900774,0.000004620075,0.00002854491,0.00005597144,0.00001338578,0.001094742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005703979,"threshold_uncertainty_score":0.01134157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004426894923448035,"score_gpt":0.2371097888204778,"score_spread":0.2326828938970298,"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."}}