{"id":"W2276461496","doi":"10.4271/2001-01-3604","title":"Numerical Investigation of Piston Speed in a Water Analog Engine on Transition to Turbulence for Experimental Modelling","year":2001,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Piston (optics); Mechanics; Mechanical engineering; Physics; Computer science; Materials science; Engineering; Optics","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":[0.0002520577,0.0002541598,0.0003659017,0.0003208763,0.0004266241,0.0004937937,0.0003566971,0.00057465,0.001167928],"category_scores_gemma":[0.0007193119,0.0001473806,0.0003127371,0.0004142302,0.0006768191,0.0003810078,0.0002648848,0.0003025448,0.0001029018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003607618,"about_ca_system_score_gemma":0.0003412228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006048482,"about_ca_topic_score_gemma":0.003718822,"domain_scores_codex":[0.9999033,0.00001487769,0.000007714073,0.00001298866,0.00003453471,0.00002650232],"domain_scores_gemma":[0.9996679,0.0002064798,0.00003001904,0.00003054614,0.00003807011,0.00002706241],"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":[0.001266037,0.0006095931,0.01502369,0.0002633489,0.0000311625,0.0009226394,0.0003728958,0.7964786,0.1672858,0.003300084,0.0005148001,0.01393133],"study_design_scores_gemma":[0.00005288525,0.0005030492,0.01054462,0.00001058458,0.00001316923,0.00005236266,0.0001370737,0.9600406,0.02799019,0.0002888887,0.0003333165,0.00003324449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947084,0.00005787867,0.002791482,0.00004218042,0.00001109198,0.00001901288,0.00008692298,0.00006546527,0.002217508],"genre_scores_gemma":[0.9986389,0.00002774998,0.0009575798,0.000003456016,0.000001115742,0.000008059347,0.00003718407,0.000004062702,0.0003219393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006048482,"threshold_uncertainty_score":0.01202655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851407140081951,"score_gpt":0.2516797273433181,"score_spread":0.2331656559424986,"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."}}