{"id":"W2346531044","doi":"10.11728/cjss2002.02.136","title":"神舟2号大气密度探测器的探测结果(I)日照和阴影区域热层大气密度变化","year":2002,"lang":"zh","type":"article","venue":"Canadian Journal of Soil Science","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thermosphere; Environmental science; Atmospheric temperature; Orbiter; Earth's magnetic field; Atmospheric sciences; Circular orbit; Altitude (triangle); Density of air; Atmospheric sounding; Physics; Orbit (dynamics); Meteorology; Ionosphere; Astronomy; Geometry; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007035289,0.0001839329,0.0002407305,0.0006648409,0.0004615415,0.0002929279,0.0007199896,0.000109449,0.0009843024],"category_scores_gemma":[0.0003000838,0.0001819148,0.0001197587,0.001379902,0.0006301259,0.0008479667,0.00001156254,0.0004755543,0.0003066362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007471876,"about_ca_system_score_gemma":0.0008137199,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01179801,"about_ca_topic_score_gemma":0.02132125,"domain_scores_codex":[0.9979341,0.00002541723,0.0005157026,0.0001734427,0.0005435382,0.0008078073],"domain_scores_gemma":[0.9974837,0.00003178854,0.0001720487,0.0002205763,0.0004502699,0.00164162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003450782,0.0001653792,0.05006761,0.0003991742,0.0002560928,0.005259192,0.03664973,0.2504666,0.04825093,0.05587689,0.08339065,0.4691833],"study_design_scores_gemma":[0.00528983,0.002007586,0.2463052,0.003339757,0.0005776024,0.006803367,0.003330847,0.5196483,0.03528132,0.01341992,0.1591404,0.00485583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7093666,0.006972347,0.0003719406,0.002104368,0.00730522,0.0001279088,0.00002665998,0.0000248387,0.2737001],"genre_scores_gemma":[0.9980375,0.0001767145,0.0001974608,0.0001632199,0.0007374968,3.165646e-7,3.18656e-7,0.00002093081,0.0006660698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4643274,"threshold_uncertainty_score":0.999929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462860628455247,"score_gpt":0.1977170376706623,"score_spread":0.1830884313861098,"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."}}