{"id":"W2948445272","doi":"10.11159/ffhmt19.145","title":"Maximizing Mass Transfer Using Highly Curved Helical Pipes: A CFD Investigation","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Spacecraft and Cryogenic Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computational fluid dynamics; Mass transfer; Mechanics; Computer science; Marine engineering; Mechanical engineering; Aerospace engineering; Materials science; Physics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001546802,0.0002644846,0.0002739484,0.0001641184,0.00005521866,0.0001055883,0.0004739525,0.0001923866,0.0001791441],"category_scores_gemma":[0.00001892281,0.0002122338,0.0001285003,0.0001668169,0.0001216848,0.000315743,0.00002815017,0.0002983327,0.00001624737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008129414,"about_ca_system_score_gemma":0.00003073184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001680472,"about_ca_topic_score_gemma":0.000002814765,"domain_scores_codex":[0.9987043,0.000005561468,0.0003245827,0.0002975716,0.0004072903,0.0002606629],"domain_scores_gemma":[0.9995872,0.00002722612,0.0000112395,0.0001130772,0.0001943155,0.00006697157],"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":[0.0000735275,0.00001336541,0.001410736,0.0001157317,0.00008751686,3.27267e-7,0.0002990965,0.0003924261,0.9715089,0.02527891,0.00007447512,0.0007450286],"study_design_scores_gemma":[0.001112641,0.00009936321,0.0005680284,0.0004492294,0.00006821128,0.00001039619,0.0006498315,0.2101642,0.7809784,0.004786945,0.0007153961,0.0003973794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878884,0.0001087426,0.002433585,0.001493564,0.0004394928,0.0003446985,0.00003008847,0.000236266,0.007025187],"genre_scores_gemma":[0.9982205,0.0002067945,0.001128414,0.00008910817,0.00006114695,0.00002920297,0.000005402307,0.00003466098,0.0002247493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2097718,"threshold_uncertainty_score":0.8654645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02665497053032182,"score_gpt":0.2183500681303968,"score_spread":0.191695097600075,"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."}}