{"id":"W3197955266","doi":"10.3390/rs13173466","title":"Oil Spills or Look-Alikes? Classification Rank of Surface Ocean Slick Signatures in Satellite Data","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; National Aeronautics and Space Administration","keywords":"SeaWiFS; Oil spill; Satellite; Computer science; Remote sensing; Data cube; Environmental science; Rank (graph theory); Data mining; Geology; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003296798,0.0001015336,0.0001417299,0.00003091818,0.00005549818,0.00002682906,0.0001191011,0.00009165626,0.0001878755],"category_scores_gemma":[0.0001816569,0.00009521002,0.00002846158,0.0004355928,0.00008379472,0.0001995061,0.0001228242,0.000139044,0.00006085277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001050389,"about_ca_system_score_gemma":0.00002553314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000383792,"about_ca_topic_score_gemma":0.0009661948,"domain_scores_codex":[0.9988242,0.0001206916,0.000265579,0.0003746987,0.0002468774,0.0001679559],"domain_scores_gemma":[0.9992184,0.00006719398,0.0001176509,0.0005237119,0.00002029809,0.00005276131],"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":[0.00002644927,0.00001769472,0.0003579009,0.00002317608,0.000004893491,0.00002444335,0.0002316411,0.003482007,0.4796089,0.000007013064,0.0001973988,0.5160185],"study_design_scores_gemma":[0.0009819713,0.00004145163,0.03435877,0.000301435,0.00003551627,0.0000612337,0.001052951,0.6332633,0.2915265,0.0001883178,0.03774622,0.0004423513],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878008,0.0001906233,0.0005949633,0.0004062185,0.0001674415,0.0000427634,0.000006619633,0.00003418,0.0107564],"genre_scores_gemma":[0.9863499,0.0005107337,0.01045309,0.0001912405,0.00002950103,1.535865e-9,0.0000490626,0.00001477447,0.002401731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6297812,"threshold_uncertainty_score":0.3882552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03715889204457328,"score_gpt":0.2716350040414746,"score_spread":0.2344761119969013,"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."}}