{"id":"W2324423652","doi":"10.2514/6.2004-3632","title":"3-D Computation of Plasma Thruster Plumes","year":2004,"lang":"en","type":"article","venue":"40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Pacific Railway (Canada)","funders":"","keywords":"Plasma; Computation; Computer science; Aerospace engineering; Physics; Engineering; Algorithm; Nuclear physics","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":[0.0003098501,0.0007494268,0.0005170851,0.0006056727,0.0007760755,0.001324711,0.000998566,0.002085436,0.005355371],"category_scores_gemma":[0.002289811,0.0008821178,0.0007459671,0.0006079852,0.0007819672,0.0007078369,0.0009648817,0.000947299,0.0005969961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197012,"about_ca_system_score_gemma":0.0008754969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01716076,"about_ca_topic_score_gemma":0.01200423,"domain_scores_codex":[0.9998844,0.00002355579,0.000006214591,0.00001610844,0.00004171283,0.00002806212],"domain_scores_gemma":[0.9993457,0.0003701222,0.00005783625,0.00003971545,0.0001034966,0.00008316467],"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":[0.00006385092,0.00002368645,0.0006984673,0.00002074229,0.00001654611,0.0001188207,0.00003638476,0.9946157,0.001183575,0.001189986,0.0003175808,0.00171466],"study_design_scores_gemma":[0.00001444082,0.000004694351,0.0001734692,0.000001936867,0.000001809668,0.000009171463,0.000009059841,0.9991032,0.000222489,0.0003108831,0.0001448367,0.000004048845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6808984,0.0006591668,0.2558424,0.001547886,0.0002661284,0.0002321215,0.002433579,0.004133786,0.05398653],"genre_scores_gemma":[0.9627802,0.0001266432,0.03241351,0.0001549438,0.00004503032,0.00008483647,0.0005032711,0.0003206385,0.003570875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01716076,"threshold_uncertainty_score":0.03412175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238786956528353,"score_gpt":0.2249454029613316,"score_spread":0.2025575333960481,"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."}}