{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001408964,0.0005759902,0.0002315398,0.000206688,0.0001741427,0.0003796766,0.0005735521,0.0004095591,0.001023452],"category_scores_gemma":[0.0004264003,0.0001599147,0.0003879646,0.0003231856,0.0003089531,0.0006385426,0.0002997144,0.000463964,0.0003773412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00034661,"about_ca_system_score_gemma":0.0003265348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001136096,"about_ca_topic_score_gemma":0.001173227,"domain_scores_codex":[0.9998963,0.00002158137,0.000003135369,0.00001773307,0.00004578325,0.00001550538],"domain_scores_gemma":[0.9998796,0.00004852534,0.00002153435,0.00001411848,0.00002871436,0.000007396892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003385638,0.00002963266,0.001118016,0.00005138679,0.00002260224,0.0002565065,0.00008547431,0.9378132,0.01982065,0.02671487,0.0006645003,0.01338927],"study_design_scores_gemma":[0.000002000645,0.00001614907,0.0001631744,0.000001804275,0.000003788845,0.00009452792,0.00000659417,0.9960697,0.0008789512,0.00252329,0.0002360947,0.000003948396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04519119,0.000185823,0.9495007,0.00009770731,0.00002645554,0.00001493678,0.00005701093,0.0001321226,0.004794049],"genre_scores_gemma":[0.9340923,0.000695752,0.05757792,0.0001048405,0.00004151505,0.00005031616,0.0001594175,0.00008271494,0.007195177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001136096,"threshold_uncertainty_score":0.00342375,"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."}}