{"id":"W7033185916","doi":"","title":"OPTIMIZATION OF CONVERGENT-DIVERGENT LAVAL NOZZLE TO
\\nPRODUCE NANO PARTICLES","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Nutrition, Health, and Society Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nozzle; Nucleation; Condensation; Drop (telecommunication); Heat transfer; Pressure drop; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001838389,0.0001691842,0.000302127,0.000009813037,0.000246619,0.00001878296,0.0001530093,0.0001633739,0.0006792273],"category_scores_gemma":[0.00006604688,0.00007040551,0.0001402212,0.0002299018,0.00002468312,0.00004594738,0.00002210454,0.00006635683,0.00004100489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002133188,"about_ca_system_score_gemma":0.00001533388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001354717,"about_ca_topic_score_gemma":0.006908898,"domain_scores_codex":[0.9987628,0.00006026747,0.0003466337,0.0003265502,0.0002729642,0.0002307754],"domain_scores_gemma":[0.9992883,0.0000696136,0.0001620593,0.00005893326,0.000312407,0.0001087179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007492132,0.001970477,0.06553178,0.001803104,0.0004786105,0.000002186632,0.01011283,0.002620487,0.4568493,0.002448598,0.4129233,0.04451016],"study_design_scores_gemma":[0.001263202,0.002987579,0.6365409,0.000609919,0.0003528879,0.000001978115,0.02930887,0.0009935226,0.1968567,0.001065789,0.1277724,0.002246157],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954575,0.0003425695,0.00001590734,0.001526518,0.0007753371,0.0003970987,0.00005399101,0.00005907518,0.001371961],"genre_scores_gemma":[0.9867269,0.002561764,0.0006079154,0.0003809968,0.0004492655,0.00005063262,0.001171418,0.000002407972,0.008048654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5710092,"threshold_uncertainty_score":0.7437062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01789684948619165,"score_gpt":0.2437114786311419,"score_spread":0.2258146291449502,"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."}}