{"id":"W3007864084","doi":"10.3334/ornldaac/1707","title":"ABoVE: AirSWOT Water Masks from Color-Infrared Imagery over Alaska and Canada, 2017","year":2019,"lang":"en","type":"article","venue":"Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Infrared; Environmental science; Geography; Optics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001620579,0.0008196176,0.0003021669,0.002240266,0.001105405,0.0009345231,0.0005354653,0.0003485207,0.007857164],"category_scores_gemma":[0.0005279223,0.0002312296,0.0003295213,0.003261648,0.0003207557,0.000500468,0.0005230767,0.0004079434,0.003639851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002861985,"about_ca_system_score_gemma":0.007177867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8972284,"about_ca_topic_score_gemma":0.9514527,"domain_scores_codex":[0.999791,0.000006447182,0.000009663996,0.00004205045,0.00009637321,0.00005451171],"domain_scores_gemma":[0.9996008,0.00001551723,0.00002712364,0.00004247553,0.0002569059,0.00005709927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000926361,0.0002982256,0.1453543,0.00102605,0.0002978035,0.001012809,0.00170555,0.01817855,0.01811729,0.002057424,0.6260895,0.1849361],"study_design_scores_gemma":[0.0001471093,0.00004778928,0.4630733,0.0003293552,0.0001014772,0.0002957859,0.003289233,0.01500462,0.009584422,0.001169991,0.50679,0.0001669416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1143483,0.0004864542,0.001693576,0.0001405423,0.00008883345,0.0001381461,0.8678567,0.002167234,0.0130803],"genre_scores_gemma":[0.1055481,0.0003314839,0.00533274,0.00003640154,0.00001439789,0.00008940037,0.8828758,0.0002683947,0.005503344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1027716,"threshold_uncertainty_score":0.2067537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003162640497364026,"score_gpt":0.1970791365713537,"score_spread":0.1939164960739897,"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."}}