{"id":"W6944780008","doi":"10.21227/rxs9-q120","title":"Source Code and Dataset associated with \"Realistic Channel and Delay Coefficient Generation for Dual Mobile Space-Ground Links -- A Tutorial\"","year":2024,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Channel (broadcasting); Code (set theory); Global Positioning System; Source code; Doppler effect; GNSS applications; SIGNAL (programming language); GPS signals; Code division multiple access","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002510279,0.001113009,0.001274914,0.0004731038,0.0004506838,0.001025925,0.0005174798,0.001167395,0.000039391],"category_scores_gemma":[0.0005964704,0.0009831099,0.00007958889,0.0005063206,0.0003828512,0.0003974303,0.000423888,0.001211129,0.0006090629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004858715,"about_ca_system_score_gemma":0.0005474833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00177262,"about_ca_topic_score_gemma":0.009830025,"domain_scores_codex":[0.9943745,0.0002274711,0.001042492,0.002280457,0.001173462,0.0009016875],"domain_scores_gemma":[0.9958257,0.0004553157,0.0009455747,0.002002602,0.0003229116,0.000447899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002620152,0.0003085629,0.000005052607,0.0003968441,0.0006749323,0.0002912957,0.000101817,0.001445219,0.0001885496,0.000005552846,0.9962942,0.00002598201],"study_design_scores_gemma":[0.001836385,0.0007247053,0.00000913817,0.0003195265,0.002631734,0.0003571767,0.00006231074,0.02118489,0.00003383668,0.00000852935,0.9716902,0.001141597],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004556327,0.0004409646,0.0007622135,0.00003902232,0.002207175,0.002970679,0.9888469,0.0001752272,0.000001512874],"genre_scores_gemma":[0.0005798237,0.0001235392,0.00009493362,0.0001680135,0.002637379,0.0009848062,0.9948757,0.0003133157,0.0002225141],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.024604,"threshold_uncertainty_score":0.9992619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03677378330446915,"score_gpt":0.2976954983658709,"score_spread":0.2609217150614018,"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."}}