{"id":"W4413209853","doi":"10.2139/ssrn.5387872","title":"Surrogate Model for Heat Transfer Prediction in Impinging Jet Arrays Using Dynamic Inlet/Outlet and Flow Rate Control","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Heat Transfer Mechanisms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Inlet; Mechanics; Jet (fluid); Heat transfer; Flow (mathematics); Volumetric flow rate; Flow control (data); Materials science; Computational fluid dynamics; Environmental science; Control theory (sociology); Computer science; Physics; Mechanical engineering; Control (management); Engineering; Artificial intelligence","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":[0.0005505447,0.000552356,0.0009792816,0.0002640706,0.0003193098,0.001054611,0.0006944389,0.001460261,0.001133189],"category_scores_gemma":[0.002336572,0.0004521426,0.0006175631,0.0004149074,0.0005858662,0.0009788171,0.0006603313,0.001218765,0.0002340133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003731411,"about_ca_system_score_gemma":0.000772878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002578183,"about_ca_topic_score_gemma":0.001328957,"domain_scores_codex":[0.9997082,0.00008935927,0.00001490833,0.00005790183,0.00009150917,0.00003809151],"domain_scores_gemma":[0.9992125,0.000459198,0.00007775248,0.00006838246,0.00013893,0.00004324166],"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":[0.00004020597,0.00002371999,0.0001942813,0.00001299635,0.00000655062,0.00001532559,0.000006516531,0.9956307,0.00120278,0.001040943,0.00008570406,0.001740257],"study_design_scores_gemma":[0.000001226472,0.000004693414,0.0000235653,3.28946e-7,3.880961e-7,8.072435e-7,4.833602e-7,0.9997061,0.0001343478,0.0001150891,0.00001216743,6.908896e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2070741,0.0002955154,0.786045,0.0002819491,0.0001229122,0.00005708958,0.0002736438,0.0004318936,0.005418017],"genre_scores_gemma":[0.9808556,0.000102464,0.01637655,0.00003739297,0.00002551231,0.00008713466,0.0002220095,0.00004420337,0.002249236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002578183,"threshold_uncertainty_score":0.005126357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000818491409483,"score_gpt":0.2297643295036372,"score_spread":0.2197561445895424,"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."}}