{"id":"W2162226412","doi":"10.1155/2012/750162","title":"The Effects of Mixing, Reaction Rates, and Stoichiometry on Yield for Mixing Sensitive Reactions—Part I: Model Development","year":2012,"lang":"en","type":"article","venue":"International Journal of Chemical Engineering","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Dimensionless quantity; Stoichiometry; Yield (engineering); Mixing (physics); Micromixing; Reaction rate; Diffusion; Chemistry; Thermodynamics; Mass fraction; Chemical reaction; Reaction rate constant; Physical chemistry; Analytical Chemistry (journal); Organic chemistry; Kinetics; Physics; Catalysis; Classical mechanics","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":[0.001126212,0.001462028,0.001133328,0.0007615613,0.000499511,0.001324504,0.00205039,0.002187823,0.003006852],"category_scores_gemma":[0.003073825,0.0007905882,0.001451226,0.0006061222,0.001046548,0.002195315,0.001113992,0.001761068,0.0008752317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001810821,"about_ca_system_score_gemma":0.000930258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003854757,"about_ca_topic_score_gemma":0.001588281,"domain_scores_codex":[0.9997599,0.00006524847,0.00001751419,0.00005807178,0.0000598998,0.00003932512],"domain_scores_gemma":[0.9991417,0.0005583648,0.0001334629,0.00006045311,0.00007611063,0.00002978935],"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":[0.00004020782,0.00005748344,0.0004730495,0.0001748662,0.0000136456,0.00009461676,0.00004648939,0.9555304,0.00946665,0.02999103,0.000355022,0.003756606],"study_design_scores_gemma":[0.000006907987,0.00001702589,0.00009488402,0.000007086544,0.000007690331,0.00001394348,0.000004078531,0.9938548,0.001536063,0.003848938,0.0005991504,0.000009342915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1353895,0.004053773,0.8235713,0.001423417,0.0001891213,0.0005264668,0.001263755,0.0006846028,0.03289818],"genre_scores_gemma":[0.8905681,0.005087743,0.07937487,0.0002734624,0.0001049621,0.002092272,0.0005494314,0.0002632503,0.02168592],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003854757,"threshold_uncertainty_score":0.01313847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110969736694265,"score_gpt":0.2424696239326557,"score_spread":0.2313726502632292,"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."}}