{"id":"W2008779204","doi":"10.1029/2012ja017866","title":"A statistical analysis of SuperDARN scattering volume electron densities and velocity corrections using a radar frequency shifting technique","year":2012,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Science and Technology Facilities Council","keywords":"Scattering; Computational physics; Radar; Ionosphere; Electron density; Refractive index; Local time; Physics; Electron; Geophysics; Atmospheric sciences; Remote sensing; Geology; Optics; Mathematics; Statistics","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":[0.00319839,0.0003326553,0.0003221249,0.001305696,0.0002982313,0.0003949601,0.0004334939,0.0002204888,0.0008014261],"category_scores_gemma":[0.01009304,0.0001352695,0.0006872579,0.001289252,0.0003697725,0.0004633081,0.0002666014,0.0004376184,0.0002191015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003596657,"about_ca_system_score_gemma":0.0004752734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003076159,"about_ca_topic_score_gemma":0.001953783,"domain_scores_codex":[0.9985216,0.0003782386,0.000085333,0.0003167495,0.0006193115,0.00007876162],"domain_scores_gemma":[0.9898273,0.006377142,0.0009640393,0.001246647,0.001472207,0.0001126236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008567424,0.0002360524,0.4139767,0.0001653902,0.001265921,0.000681324,0.0006359578,0.1060139,0.06084189,0.01345148,0.002712958,0.3991616],"study_design_scores_gemma":[0.00002148799,0.0005690155,0.5534631,0.00001661444,0.0001710466,0.0004975022,0.0002255052,0.4179052,0.01946013,0.002518056,0.005068798,0.00008355089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7577718,0.0001583091,0.2385449,0.00006647938,0.00004974178,0.0001119692,0.000854214,0.0006573763,0.001785157],"genre_scores_gemma":[0.9611723,0.00006888881,0.03675761,0.00001558803,0.0000304819,0.00007455281,0.001176158,0.00006521914,0.0006392731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00319839,"threshold_uncertainty_score":0.0169149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035549717648627,"score_gpt":0.3165781449760219,"score_spread":0.2962226477995356,"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."}}