{"id":"W2781534925","doi":"10.1063/1.4996719","title":"Marginal stability, characteristic frequencies, and growth rates of gradient drift modes in partially magnetized plasmas with finite electron temperature","year":2018,"lang":"en","type":"article","venue":"Physics of Plasmas","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Russian Science Foundation; Ministry of Education and Science of the Russian Federation","keywords":"Physics; Gyroradius; Instability; Plasma; Two-stream instability; Marginal stability; Magnetic field; Plasma oscillation; Diamagnetism; Atomic physics; Electron; Electric field; RADIUS; Electron temperature; Wavelength; Collision frequency; Condensed matter physics; Computational physics; Mechanics; Optics; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008402928,0.0001841056,0.0002939829,0.00005631906,0.0000359376,0.00002253817,0.0001250173,0.00005856732,0.000006146523],"category_scores_gemma":[0.0000444353,0.0001692628,0.00002712669,0.0002468343,0.000205953,0.0001099723,0.00002666551,0.0001605137,0.000003194676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002537005,"about_ca_system_score_gemma":0.00004765947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005050402,"about_ca_topic_score_gemma":0.0004040469,"domain_scores_codex":[0.9991313,0.00001830461,0.0002617516,0.0001977369,0.0001445365,0.0002463983],"domain_scores_gemma":[0.9992982,0.000253109,0.00007558329,0.0001872784,0.0001236793,0.00006221571],"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":[0.0002636187,0.0004460954,0.04484165,0.0006344517,0.0001252995,0.000007105344,0.001352091,0.007579492,0.8798679,0.06446686,0.0001371406,0.0002782935],"study_design_scores_gemma":[0.0007747528,0.000317177,0.02717554,0.0001167966,0.00004289084,0.000002762402,0.00004694478,0.04438624,0.9203922,0.006414541,0.00006811844,0.0002620927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987872,0.00004181569,0.0002732342,0.00006899481,0.00002877698,0.0002166195,0.0001831133,0.00003246458,0.0003677759],"genre_scores_gemma":[0.9980853,0.0001181345,0.001606432,0.000006294762,0.00005073638,0.00004902394,0.00005348721,0.00002418541,0.000006386139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05805232,"threshold_uncertainty_score":0.6902338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105244446769518,"score_gpt":0.2072808487833755,"score_spread":0.1967564041064237,"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."}}