{"id":"W2032706259","doi":"10.1109/radar.2013.6585990","title":"Sea surface oil slick detection from GNSS-R Delay-Doppler Maps using the spatial integration approach","year":2013,"lang":"en","type":"article","venue":"","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"GNSS applications; Remote sensing; Doppler effect; Computer science; Wind speed; Sampling (signal processing); Environmental science; Geodesy; Geology; Meteorology; Computer vision; Filter (signal processing); Global Positioning System; Geography; Physics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003211064,0.0003540412,0.0002094381,0.0009106116,0.0001709983,0.0003662327,0.0002775516,0.0001198749,0.0007321645],"category_scores_gemma":[0.001233682,0.0001541045,0.0003435714,0.0006332727,0.0002180653,0.0004433634,0.0003986261,0.0002026348,0.0002167657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003002626,"about_ca_system_score_gemma":0.0007674397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005994747,"about_ca_topic_score_gemma":0.006947492,"domain_scores_codex":[0.9998265,0.00003016881,0.000009994311,0.0000264273,0.00008964197,0.00001727048],"domain_scores_gemma":[0.9998342,0.00004578355,0.00002590479,0.00001778199,0.0000703765,0.000006005306],"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":[0.0001307458,0.00006011584,0.009620455,0.0001538121,0.00009485425,0.0001545158,0.0001807692,0.3625052,0.09809022,0.01355952,0.0006196267,0.5148302],"study_design_scores_gemma":[0.0000077706,0.00003744625,0.005464856,0.00001068491,0.00002113018,0.0000780002,0.00004262921,0.9735895,0.01682341,0.002408807,0.001500061,0.00001580683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08053325,0.0001044068,0.9163232,0.00005073255,0.0000164869,0.0000257514,0.00007106949,0.000546939,0.00232819],"genre_scores_gemma":[0.5389789,0.0001791637,0.4595809,0.00002285787,0.00001661639,0.00003431582,0.0002108858,0.00007493419,0.0009014454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005994747,"threshold_uncertainty_score":0.01191968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405929505893331,"score_gpt":0.2039773200362088,"score_spread":0.1899180249772755,"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."}}