{"id":"W2546775350","doi":"10.1109/lgrs.2016.2618855","title":"First-Order Bistatic High-Frequency Radar Power for Mixed-Path Ionosphere-Ocean Propagation","year":2016,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bistatic radar; Clutter; Radar; Ionosphere; Radar horizon; Remote sensing; Radar imaging; Geology; Computer science; Geophysics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002607188,0.0001836818,0.0001822295,0.00007058748,0.0002967904,0.0001133459,0.0000961066,0.00006088911,0.000002039405],"category_scores_gemma":[0.00004964513,0.000125942,0.00003942161,0.0002162794,0.0001534977,0.0003227011,0.000008477834,0.00006811442,0.000006597691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006568753,"about_ca_system_score_gemma":0.00002702066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001534365,"about_ca_topic_score_gemma":0.000027915,"domain_scores_codex":[0.9988127,0.00001969599,0.0002551318,0.0003150479,0.0002129812,0.000384388],"domain_scores_gemma":[0.9995227,0.00008295715,0.00006726834,0.0001725609,0.00006594483,0.00008850952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001201569,0.000007073013,0.00006646159,0.0003355157,0.00002434521,0.00003385993,0.000761521,0.001072666,0.8475499,0.00006539867,0.003953388,0.1461178],"study_design_scores_gemma":[0.005671335,0.0005876361,0.005849922,0.007167303,0.0001843398,0.0007179047,0.0009708673,0.8390798,0.107066,0.007605993,0.02064045,0.004458454],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.463813,0.00007313747,0.533801,0.001107719,0.0009067681,0.0001527533,0.000003823245,0.00009651992,0.0000452622],"genre_scores_gemma":[0.9360428,0.00002003461,0.06326112,0.0003637422,0.0001439442,1.836042e-7,0.000001153828,0.00003129679,0.0001357443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8380072,"threshold_uncertainty_score":0.5135767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006390484327123737,"score_gpt":0.1920393579592434,"score_spread":0.1856488736321197,"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."}}