{"id":"W4280515971","doi":"10.3390/jmse10050649","title":"First-Order Ocean Surface Cross Section for Shipborne Bistatic HFSWR: Derivation and Simulation","year":2022,"lang":"en","type":"article","venue":"Journal of Marine Science and Engineering","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Bistatic radar; Radar cross-section; Doppler effect; Radar; Surface wave; Geology; Physics; Acoustics; Computer science; Telecommunications; Optics; Radar imaging","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":[],"consensus_categories":[],"category_scores_codex":[0.0008760202,0.00005834372,0.00008374522,0.0001002506,0.0004125497,0.0001162838,0.00006016666,0.00001226651,0.00002572101],"category_scores_gemma":[0.0001724277,0.00004949873,0.0000160033,0.0003306333,0.00004759522,0.0004143416,0.00002937133,0.0001029209,1.095997e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001439111,"about_ca_system_score_gemma":0.00003891398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005342271,"about_ca_topic_score_gemma":0.0000126177,"domain_scores_codex":[0.9993361,0.000007038628,0.000168759,0.00009670288,0.000250356,0.0001410338],"domain_scores_gemma":[0.999582,0.0001033713,0.00008040274,0.00003591244,0.0001290361,0.00006926117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001993238,0.000002599321,0.01686386,0.00002594389,0.000003015638,0.000001769253,0.0001400731,0.9750943,0.0002167166,0.000005349762,0.000008429568,0.007618025],"study_design_scores_gemma":[0.0001917743,0.0001331348,0.1891312,0.000007604068,0.000005371563,0.00007010437,0.0001080785,0.8092895,0.00002504445,0.00009286052,0.0008904003,0.0000549529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99648,0.0000837812,0.002713776,0.0001615311,0.0004539989,0.00005939344,0.000002720151,0.000007035116,0.00003774047],"genre_scores_gemma":[0.9924853,0.00003107906,0.00731622,0.00002812945,0.0001043314,3.174918e-9,0.000002713141,0.000002491621,0.00002969762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1722673,"threshold_uncertainty_score":0.317304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00968072500819462,"score_gpt":0.2165245455795031,"score_spread":0.2068438205713085,"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."}}