{"id":"W2325501798","doi":"10.3390/rs8040315","title":"AVHRR GAC SST Reanalysis Version 1 (RAN1)","year":2016,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Climate variability and models","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration","keywords":"Advanced very-high-resolution radiometer; Environmental science; Meteorology; Climatology; Brightness temperature; Sea surface temperature; Remote sensing; Pathfinder; Atmospheric radiative transfer codes; Radiative transfer; Satellite; Brightness; Geology; Computer science; Geography; 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":[0.002469703,0.00117387,0.001143756,0.0020137,0.0005818165,0.001337395,0.001848618,0.0004476885,0.006399238],"category_scores_gemma":[0.002616188,0.0004231028,0.0007233553,0.004908169,0.0002284169,0.0009236469,0.0008259715,0.001313323,0.005873243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001277228,"about_ca_system_score_gemma":0.004623811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1215263,"about_ca_topic_score_gemma":0.0990659,"domain_scores_codex":[0.9986368,0.0001952009,0.00009969999,0.0003132208,0.0005984544,0.0001566888],"domain_scores_gemma":[0.9974312,0.000115925,0.0002788133,0.0004613205,0.001601507,0.0001112485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009699207,0.0002098985,0.05362199,0.001834815,0.0009875143,0.0002319058,0.0005002806,0.02334376,0.01482114,0.006712747,0.6659626,0.2308033],"study_design_scores_gemma":[0.0003666197,0.0001238876,0.2082521,0.0002762926,0.0002765415,0.0001075718,0.0001749819,0.01859144,0.007362538,0.001724471,0.7625728,0.0001707203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.044241,0.002048778,0.01521676,0.0008382027,0.0008800429,0.0004966033,0.8992367,0.01063345,0.02640846],"genre_scores_gemma":[0.06656343,0.001305852,0.03947916,0.0003366492,0.0002282138,0.0007671777,0.8784709,0.001997686,0.01085101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1215263,"threshold_uncertainty_score":0.2416378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476097631545315,"score_gpt":0.2240418303843117,"score_spread":0.2092808540688585,"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."}}