{"id":"W1956334341","doi":"10.1109/cvprw.2015.7301386","title":"Oil spill candidate detection from SAR imagery using a thresholding-guided stochastic fully-connected conditional random field model","year":2015,"lang":"en","type":"article","venue":"","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Thresholding; Conditional random field; Oil spill; Computer science; Field (mathematics); Artificial intelligence; Random field; Oil field; Random forest; Remote sensing; Computer vision; Pattern recognition (psychology); Geology; Image (mathematics); Statistics; Mathematics; Petroleum engineering","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":[0.0008933491,0.0009117338,0.001052955,0.0009314611,0.0004190417,0.0006080748,0.002427366,0.001377921,0.001055044],"category_scores_gemma":[0.002619418,0.0007054462,0.001193488,0.0006707119,0.001030791,0.0009118041,0.0007190713,0.001214559,0.0002646238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092342,"about_ca_system_score_gemma":0.001094408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01750454,"about_ca_topic_score_gemma":0.01780118,"domain_scores_codex":[0.9996194,0.000101295,0.00001452449,0.0001356256,0.00007419972,0.00005489918],"domain_scores_gemma":[0.9989237,0.0006738614,0.0001319996,0.00006676641,0.000153941,0.00004967396],"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":[0.0000932902,0.00003897692,0.000834998,0.00003672681,0.00003573883,0.00009814704,0.00003888959,0.9669448,0.002368775,0.004294279,0.0006944743,0.02452084],"study_design_scores_gemma":[0.000001969892,0.000003404551,0.00008208443,0.000001446433,0.000002704082,0.000006839596,8.542954e-7,0.9988157,0.0001842206,0.0008610865,0.00003650246,0.000003199088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05019049,0.0001720131,0.9476791,0.0003286415,0.00002198637,0.00004443503,0.0001854844,0.000685019,0.0006927534],"genre_scores_gemma":[0.8126249,0.0002181316,0.1826308,0.000275771,0.000061106,0.0001658776,0.001002555,0.0001534838,0.002867339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01750454,"threshold_uncertainty_score":0.0348053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03013387623714096,"score_gpt":0.2552398108269521,"score_spread":0.2251059345898112,"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."}}