{"id":"W2170461243","doi":"10.1109/tgrs.2006.883461","title":"Computing Coastal Ocean Surface Currents From Infrared and Ocean Color Satellite Imagery","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration; University of British Columbia","keywords":"SeaWiFS; Remote sensing; Moderate-resolution imaging spectroradiometer; Advanced very-high-resolution radiometer; Ocean color; Satellite; Satellite imagery; Image resolution; Sea surface temperature; Infrared; Geology; Environmental science; Radiometry; Climatology; Physics; Optics","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":[0.000390665,0.0001975659,0.0001947292,0.00004498285,0.000764503,0.000167374,0.00009477053,0.00007972356,0.00001683645],"category_scores_gemma":[0.000009561133,0.000168248,0.0000441914,0.0005346781,0.0004834108,0.0003454364,0.000002125152,0.0002412,0.000007288652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000363713,"about_ca_system_score_gemma":0.00004618264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00202726,"about_ca_topic_score_gemma":0.0006876977,"domain_scores_codex":[0.9985561,0.00003741854,0.0002548941,0.0004487885,0.0002664839,0.000436283],"domain_scores_gemma":[0.9992049,0.0003003403,0.00008690055,0.0001238127,0.00005143833,0.0002326637],"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":[0.00005524496,0.0000151934,0.007044348,0.00001976547,0.00001268352,0.00003699482,0.0006377118,0.001146791,0.0002327636,3.007035e-7,0.0000127449,0.9907855],"study_design_scores_gemma":[0.0008519677,0.0002985335,0.1658345,0.0003644445,0.00007591519,0.0001863577,0.003577507,0.8208364,0.005537568,0.0006031648,0.001029185,0.0008044484],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7832012,0.0004532892,0.215269,0.00005567984,0.0005177896,0.00008316674,0.00003902887,0.00006694593,0.0003139738],"genre_scores_gemma":[0.9673394,0.0007180264,0.03152731,0.0002114336,0.00004853239,4.062904e-10,0.000008407971,0.000005174757,0.0001417438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.989981,"threshold_uncertainty_score":0.6860954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010609616311087,"score_gpt":0.2171659693643646,"score_spread":0.2070598732012538,"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."}}